AI Ethics in Action

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AI Ethics in Action: A practical guide to building modern organizations through purposeful, ethical AI innovation

Welcome to Packt Early Access. We’re giving you an exclusive preview of this book before it goes on sale. It can take many months to write a book, but our authors have cutting-edge information to share with you today. Early Access gives you an insight into the latest developments by making chapter drafts available. The chapters may be a little rough around the edges right now, but our authors will update them over time.You can dip in and out of this book or follow along from start to finish; Early Access is designed to be flexible. We hope you enjoy getting to know more about the process of writing a Packt book.

Chapter 1: A Brief Primer on Ethics

Chapter 2: Moving from Ethics to AI Ethics

Chapter 3: Doing Ethics: Overcoming Objections

Chapter 4: Rejecting Ethics: Washing Our Hands of This

Chapter 5: The Trustworthiness of AI (Risk-based Framework)

Chapter 6: AI In the Wild (Rights-based Framework)

Chapter 7: AI like Me? (Relational-based Framework)

Chapter 8: Utilizing the Frameworks

Chapter 9: Complications of Owning AI

Chapter 10: Lawlessness and the Regulation Landscape

Chapter 11: Navigating Future AI Developments

Chapter 12: Next-Generation Ethics

Chapter 13: Human Rights in a Global AI Landscape

Chapter 14: Navigating Global AI Governance: Ethical Leadership and Accountability

Chapter 15: Best Practices

Chapter 16: Conclusion

Chapter 17: A Continuation of Now

Chapter 18: The Good Enough Thesis

1 A Brief Primer on Ethics

Ethics and technology have always had a long and complicated history. Artificial Intelligence is no exception to ethical challenges or the debates surrounding them. Due to both the reach and speed of this technology, the call for ethics has intensified as harms and challenges match the speed and reach of the innovation itself. The calls to mediate the challenges are immense, from international to local regulations. At the same time, many fear that attempts to protect ourselves from our technology will fail as it has in the past from chatbots, social media, video games, and the most powerful innovation yet – generative AI. The time for AI ethics is now, if only we knew and understood how to do ethics.Ethics speaks to people's decisions as they are right, good, fair, and just. To you, these decisions often seem subjective or impossible to fully understand by others outside the view of the person who made the choice. First, you will explore varying drivers (theories) of ethical behavior and gain an understanding of how and why people make ethical choices. Then, you will learn of objections to ethics that further complicate making good choices. Finally, you will be shown how this disagreement regarding theories can create more effective dialogue regarding prioritizing issues and challenges.In this chapter, we’re going to cover the following main topics:

Introducing ethics and ethical theories

Understanding deontological ethics

Looking at Consequentialist Theory

Exploring character through Virtue Ethics

Understanding the importance of Ethics in AI

Introducing ethics and ethical theories

Ethics is the study of the concepts, theories, systems, rules, principles, and values of what is morally good or bad or right or wrong. In comparison, morality determines the standards of what is right or wrong and good or bad. When situations are difficult and contain an element of good and bad, they are called moral dilemmas. Difficult questions often reveal a moral dilemma, but the answers reveal how we make moral judgments. These judgments then reveal the moral rules that underpin the decision.A moral principle or rule might be to do no harm, provide justice, or ensure the protection of people. Of interest, an Oxford University study of 60 cultures determined seven universal moral rules: “Help your family, help your group, return favors, be brave, defer to superiors, divide resources fairly, and respect others’ property…” (Seven moral rules found all around the world, 2019). This reveals that it is possible to find consistency or common ground within morality.Philosophers who study ethics and morality have determined that three basic moral theories sum up our moral decision-making. Each has its own principles and governing ideas. When we review our moral choices, we can identify which moral theory we are using and the principles that we value that support those choices.So, to begin our work in ethics, please answer the following questions, then tally your A, B, and C answers. Later in this chapter, you’ll learn which of the three moral theories you lean toward when making decisions and if your principles change depending on your question.

Quiz

What kind of moral decision-maker am I?

You comply with strict privacy regulations, but your clients want even more. What do you do?

Educate your customer on how you are complying.

Look for ways to boost privacy.

Ask yourself how a good company should respond.

You have an existing app, but to improve it, you need data. Do you…

Change the terms of service and gather the data.

Change the terms of service with notification and opt-in settings.

Attempt to balance the needs of the business and clients.

You have a business name close to a competitor’s name. You…

Don’t stress because you know legally you are in the clear.

Consider whether you should change the name based on the situations of both businesses.

Should you be a good person and change your name?

You find money on the street outside your building. You…

Drop it at the front desk; anything else is stealing.

Try to find out who it belongs to or leave it at the desk – if the owner can’t be found, you’ll donate the money.

Do what a good person would do and follow that advice.

A friend and you deeply disagree politically, and they bring up a sensitive topic. You…

Refuse to discuss it; you don’t talk about those things.

Attempt the conversation but drop the topic if others get upset.

Consider what a good friend would do and opt to do that.

You don’t believe in corporal punishment, but a friend has shared they do. You…

Listen as they advocate for their right to discipline their children.

Suggest other methods of discipline where no physical punishment is involved.

Work out a solution based on what a good parent would do.

Your child was accused of cheating. You…

Lay down the law – there are rules for a reason.

Try to understand what happened and determine a consequence that fits the situation.

Determine how to reinforce to your child that honesty is important.

You cut someone off in traffic, and they angrily gestured at you. You…

Drive more carefully; you know the rules of the road.

Drive more carefully; everyone deserves to be safe.

Resolve to become the best driver you can be.

A friend worries they need an abortion and wants you there to support them. You…

Refuse to go on the grounds it is wrong to end a life.

Examine the situation from all sides to determine the best action.

Try to be the best friend possible and seek guidance from trusted friends or people you respect for advice.

You are offered a dream job that involves relocating. You…

Verify what expenses they will pay and what you will be paying.

Consider the impact on you and your partner, your friends, and your family.

Ask someone else for advice because you are unsure.

Now that you have completed the quiz, be sure to tally up your answers so that you know which theories you are using when making moral decisions. This is an essential part of understanding your decisions, but also the decisions of those who disagree with you. Recognizing what matters to those you disagree with is even more important in negotiating and resolving moral dilemmas. Once you learn what drives complicated choices, material conversations become possible.Answers: Mostly As – Deontological Ethics, Mostly Bs – Consequentialist Ethics, Mostly Cs - Virtue EthicsLet’s now understand these ethical theories in the upcoming sections.

Understanding deontological ethics

Immanuel Kant’s deontological theory is a theory that hinges on rationalism. In other words, you must use reason to determine what is right. So, if you think deeply about moral choices, you will know what to do. For Kant, the correct or right moral choice should be constant to overcome religion's subjective challenge. And if moral choices are constant, we can understand them as moral truths or absolutes. This means that moral truths exist. This also means that the focus of a moral dilemma must be on the act we wish to do rather than the consequences or fallout of a decision. We must first understand Kant's view to consider how this might be possible.Imagine that you are faced with a person who is impoverished and, in desperation, takes food from a local grocery store. Many might claim that taking the food under desperate circumstances is moral. However, if you think about this scenario, what is actually being asked is if a person should be able to take what they want from others. It does not matter if the grocery store is large and can easily absorb the loss (expense) of taking the food or if the person is hungry or desperate. The accurate question we arrive at after thinking through this scenario is if we should all agree to live in a world where when people want something, they take it. The moral question was whether stealing should be permissible. Poverty, the grocery store size, the ability to overcome the loss of product, and other rationalizations are attempts to avoid the true question regarding stealing and speak to variable consequences.Yet, not all choices hinge on what is right; instead, we focus on what we want or desire. For instance, you might work late one night for more free time over the weekend. This decision may be the right thing to do, but it does not have moral weight. Kant referred to these as hypothetical imperatives, focusing on what to do when you want something. These should be considered a more practical choice rather than a moral one. They can also be recognized because the action is not required; you could choose to work on the weekend instead or find a third option.Categorical imperatives are those related to moral choices you must make, even when you prefer to do something else. “Categorical because it does not depend on anyone’s particular desires and an imperative because it is a command of reason.” (Cahn, 2018). This means we are all bound to follow moral law even if we don’t want to. To understand which imperative you are facing, rational thought will lead you to the correct conclusion. To explain this idea, Kant used formulations of the imperatives.The first formulation is that we must only follow the moral rules (maxims) that we would choose to be universal. Our earlier example of stealing fits this rule because determining that people may violate the maxim of not stealing would lead to stealing as a morally good or right thing. For most, that makes little sense. It would also mean that no one could be held accountable for stealing.

Categorial Imperative: Universality

Act only on those maxims (rules) that you would will to be universal (Cahn, 2018). To will something is to have the ability to make a choice. So, to will that a thing should be made universal is to choose whether it is right or wrong without contradiction (sometimes right or wrong).

The second formulation is grounded by a sense of duty that Kant believes that we all have toward others. Through our duty to others, we must ensure that people are respected as having their aims, desires, and needs that they must be allowed to pursue for themselves. It cannot be that we use people wrongly to facilitate our desires and needs while ignoring theirs. This is the foundation for the second formulation that states that we must only use people as ends and never as a means. This is called the formula of the End in Itself and is explained by Kant as follows:

Categorical Imperative: End in Itself

Act in such a way that you always treat humanity, whether in your own person or in the person of any other, never simply as a means but always at the same time as an end. (Cahn, 2018)

It is fair to say that we sometimes use people as a means, such as when we go to the bank, and the teller gives us our funds. So, some clarification is needed on when we may use someone to forward our ends and when it is wrong. “To use someone as a mere means is to involve them in a scheme of action to which they could not in principle consent” (Cahn, 2018). This means that when the other person agrees with full disclosure to assist you, you are not using them. When you omit details that might make them refuse to be involved in your scheme of action, you are using them merely as a means (wrongly). This prohibits deception, coercions, lies, half-truths, and so on.The sticking point for most people when introduced to Kant’s theory of deontology is the universality condition. Many people support exceptions to rules or the idea that rules are made to be broken. Kant accepts neither, instead demanding that we should only follow those rules we want others to follow. This is not the same as following the golden rule where we treat others as we’d want to be treated because that would mean that if you felt you deserved an exception, you should grant them to others, too. And Kant would have none of that. Instead, Kant expects everyone to be held to the same standard without aberration, even to claim the moral high ground.It seems right to challenge Kant on the claim that sometimes we must sacrifice our moral truths to bring about a greater good. For example, consider this version of a popular example:The police knock on your door and ask if you are hiding your friend. You have chosen to do so, believing that evidence can be found to exonerate them – you believe they are innocent. You reply to the police that you have no idea where your friend can be found and end the conversation. Unfortunately, the friend overheard what you said and attempted to run away but was caught two blocks from your house. (Green, 2016) If you had told the truth, the police might have searched where you said your friend was hiding (in the bedroom closet) while your friend slipped out the door. However, your lie changed how the situation played out, making you responsible for the outcome – not the police or your innocent friend – but you despite your good intentions. So, if your friend were harmed in their apprehension, their harm would be your fault. For Kant, the responsibility lies with the person who lied.The default objection to deontology is that ignoring extenuating circumstances (consequences) and focusing only on an act seems wrong. Surely, suffering or troubling situations lead a person to make a wrong choice. It is also possible to want a universal rule that others would agree to but still seem wrong. People often want wrong things, and the idea that the only moral rules are those where the majority rules seem problematic. Lastly, when focusing on duties to others, what should someone does when they have a duty to many people?In conclusion, Kant’s deontology is a rule-based moral theory that focuses on making moral choices focused on universal acceptance and duty to others. This theory focuses on the act or choice rather than the consequences. And it holds that responsibility for moral outcomes lies with people who violate moral rules through their actions. This view can seem cold or uncaring of others or dismissive of the challenges of making moral choices in our modern world, specifically because there are no exceptions or excuses to allow deviation from moral rules (Further reading, Resources 1 and 3).There is another view that considers the complexity of choice-making and the consequences that our most difficult choices bring, we will explore that next.

Looking at Consequentialist Theory

Utilitarianism, or the theory of utility addresses the concerns regarding consequences that deontology avoids – while disregarding the intentions behind moral actions. This moral theory claims that good consequences make good moral choices. So, to make good choices, we must have a method of evaluating the consequences of our actions. And we can evaluate these consequences by determining how much happiness can be gained from them. Happiness, then, is the end that all our choices and actions are directed toward. So, the foundation of this view is to seek pleasure and avoid pain.This view does not focus on egoistic concerns such as doing what a person wants for themselves so that they end up better off. Instead, it is often considered a hedonistic theory because of the emphasis on pleasure and the reduction of pain equating to happiness. However, the strength of the utility (happiness) theory is that it focuses on the maximum happiness for as many people as possible. This is known as the greatest happiness principle:

The Greatest Happiness principle

“We should act always so as to produce the greatest good for the greatest number.” (https://legaldesire.com/benthams-utilitarianism-theory-scope-criticisms/)

It is important to note that to determine how much happiness can be gained from a consequence, we must have a unit of measure for happiness. A hedon is a unit of pleasure, and a dolor measures pain. We must determine the number of hedons connected to a consequence to evaluate it. For instance, if you have not seen your family in a long time, you may consider its value 100 hedons. On the other hand, if seeing them is hurtful, the visit might have a value of 100 dolors. There may also be many sub-consequences that can be similarly broken into hedons and dolors until we arrive at a final determination and prescribed action. Sometimes, this calculus leads to easily followed actions and other times, the answer is problematic.The challenge with providing happiness for others (and situating your needs as no more important than others) is that you may have to act in a way that is not your preference or does not suit your desires so the greater good will prevail. For example, imagine that you want to visit with friends. You were hoping for a relaxed evening with a great dinner and conversation. However, your friend group wanted to go to a concert. Ultimately, you decide to support the others in going to the concert. It wasn’t what you wanted but it would make everyone else happy.Still, it seems that making choices to suit everyone rather than yourself could be problematic. To remind us that our own desires still only get one vote, utilitarians accept that they must assume the role of someone who is disinterested and merely watching situations unfold. This vantage point will allow me to table my feelings and opinions on the matter and to witness events rather than consider myself a participant. This should help eliminate bias and truly suggest what is best for everyone.One challenge related to this theory is that it may result in choices that violate your moral views. For instance, imagine you are at a bank, and a gunman comes in to rob it. You can select someone to be killed if the bank doesn’t give them the money. You believe it’s wrong to kill, but selecting a person means saving twenty others. Under the utility theory, the right thing to do is to choose a person to sacrifice to save others – even though you disagree with killing.This traditional view of utilitarianism is called act utilitarianism. This is the view that we have been discussing. It can be summed up as follows:

Act utilitarianism

“An act is right if and only if it results in as much good as any available alternative” (Cahn, 2018).

There is another form of utilitarianism, rule utilitarianism. It is explained via the following quote:

Rule utilitarianism

An act is right if and only if required by a rule that is itself a member of a set of rules whose acceptance would lead to greater utility for society than any available alternative” (Cahn, 2018).

This more expansive view looks to scale happiness over the long term. (It differs from deontology, which deems that rules should be universal and recognize our duty to others.) These rules would be focused on ensuring consequences led to happiness for the greater society. For instance, while it might be appropriate to sacrifice one person to save 20 hostages, we likely would not want to give surgeons permission to harvest organs from healthy patients, even if they could save more ill patients.It is difficult to imagine anyone objecting to a view that promotes happiness. Especially one that can respond to any dilemma while promoting happiness and minimizing pain. Utilitarianism does have its detractors who have launched serious objections to the view. Here, we will briefly discuss five of the most popular mentions (Cahn, 2018):

The no-rest objection objection: If we must always add happiness to the world, no matter what we do, we could do more or something better.

Response: Invoke a rule allowing rest or a reprieve, which would also maximize utility.

The absurd implication objection: We may have to tackle some rather absurd challenges, such as having a tie between the truth and a lie.

Response: To be honest, sometimes a lie is called for, so perhaps this concern reveals an accurate look at dilemmas.

The integrity objection: Sometimes, we may have to violate our moral code and commit acts we would rather avoid.

Response: This is also the case sometimes, and avoiding it is impossible.

The justice objection: Situations may call for us to have a casual view of justice or rights. After all, if the math reveals that violating rights will add the most happiness, then we must commit the rights violation.

Response: We may have to violate or balance rights against the greater good.

The publicity objection: You must know moral principles to follow them. Yet, utilitarians do not hold that everyone should follow the principles of utility due to the deliberation involved.

Response: If others are to follow this moral view, the rules or guidance must be known and made publicly available. And we do this through laws and legislation. This objection is applicable only to act utilitarianism.In closing, Utilitarianism is a view of the good being added to the world, and it is hard to think of that as problematic. Still, the challenges of the calculus (tallying hedons and dolors) and determining the consequences to be evaluated, only to arrive at choices that might have us acting in ways never imagined, complicates this theory (and our acceptance of it). Further, we may often be required to take actions that seem to violate our own deeply held beliefs in favor of the happiness of others. Such self-sacrifice can challenge us to accept this view as pragmatic and worthy. You can explore more about this from Resource 2 in the Further reading section.We have discussed the clarity that comes with a rule-based approach (deontology) and now a consequence-based approach in utilitarianism. But we have said little about the person making the choice or how their character can influence their choices.

Exploring character through Virtue Ethics

Aristotle’s virtue ethics is a third moral theory that should be considered. Virtue ethics holds that it is possible for someone to become a person who can always act from virtue through doing, saying, and acting correctly for the circumstances. And that a person who can do these things is considered virtuous (to act morally or correctly) and has good moral character. This theory does not get bogged down in consequences like utilitarianism or rules like deontology. Instead, this theory focuses on the person choosing the action and the qualities a good moral person should have – it is about a person’s character.From this idea of being a person of good character, it follows that good people make good choices and decisions. Still, we must learn how to be good people to make good choices, but Aristotle argues that this is possible and that it is what we are meant to do if humanity is to flourish or live well (Cahn, 2018). But to act in accordance with our nature and flourish, we must recognize that virtues are character traits that will assure good behavior once developed. These virtues sit at the midpoint between two extremes or vices. By acting from the middle, or golden mean, we learn to become good people and make good choices. In the example in Figure 1.1, we avoid both the extremes of victimhood and aggression (vices) to end up at assertiveness (golden mean).

Figure 1.1 – The golden mean

Imagine someone who is often bullied and refuses to stand up for themselves. They are often mistreated and suffer because they cannot establish good boundaries; this is not the path to human flourishing. Aggressive people will also fail to flourish due to ongoing conflicts and stress in their interactions. However, an appropriately assertive person can flourish because they are neither the victim nor the aggressor. In addition, Aristotle also claimed that the golden mean (the midpoint between two vices) would be different for different situations. For instance, being assertive seems correct under many circumstances. Still, when faced with a person who is both strong and angry, it might be that the golden mean would be closer to pacifism because calming the situation seems to be the better idea. Virtue ethics allows for this intuitive understanding of circumstances of informing right actions.

The Golden Mean

“… It is a mean between two vices, the one involving excess, the other involving deficiency, and it is such because its character is to aim at what is intermediate in passions and actions…” (Cahn, 2018).

This seems to mean that virtue ethics cannot be learned and is more intuitive since responses must be tailored to every situation. Fortunately, Aristotle assures us that it is possible to learn to be virtuous, but you must do so by practicing acting from the golden mean. In other words, this is a practical skill and wisdom. Aristotle would certainly subscribe to the idea that practice makes perfect when it comes to virtues.Before acting upon the virtues, the golden mean between two vices, we must remember that our mind is engaged in recognizing the vices, identifying the golden mean, and evaluating the circumstances before acting. So, virtue ethics requires both the mind and practice to be realized. Yet, the temptation to give in to the vices may be quite strong as we learn to act from virtue. Fortunately, virtue ethics allows us to identify a moral exemplar whose actions we can copy or mimic while still learning to be virtuous. Moral exemplars can be grandparents, religious figures, or even a best friend if they have learned (more than you) how to act from virtue. With practice, recognition, and exemplars as guides, appropriate responses will become part of your character, making you virtuous.But why should we embrace this idea of virtue? The answer is to flourish as human beings and to live as we should among each other and the world. Eudaimonia, human flourishing, is a life that involves lessons, effort, determination, growth (emotionally and psychologically), and facing the struggles and challenges of being human. Virtue ethics is not intended to resolve those challenges but to help humanity thrive despite them.Proponents of virtue ethics claim that the benefits of this theory are that anyone can become virtuous, that each situation is given appropriate attention, and that it focuses on helping people become better, leading to a changed world. Detractors are concerned that no recommended actions are provided and that the theory is too vague to be practical.It is important to remember that Aristotle’s virtue ethics focuses on the person making the choice in a moral dilemma rather than the consequence or the act itself. This theory encourages people to become better and learn to be moral rather than merely demanding it or providing rules to ensure it. It also seeks for humans to flourish and lead the lives meant for them through the nature of being human. That means a life with struggles, achievements, and challenges (including the challenge to be moral). It also expects us to do the work to remain distant from vices while leaning into virtue, with help from moral exemplars (examples) to guide us as we grow into our virtuous selves (Resources 4 and 5 in the Further reading section).It is not unreasonable for some to believe that ethics cannot be deduced into three moral theories, we explore these doubts next.

Identifying challenges to ethical theories

The three moral theories discussed maintain that there is a unifying theory of morality that can be accepted or understood, though not everyone believes this is the case. Those who disagree commonly fall into three categories: cultural relativism, subjectivism, and skepticism. While we will not discuss these in as much depth, they are worthy of consideration. After all, not everyone will believe that they fit into one of the three categories above. But as with utilitarianism, deontology, and virtue ethics, these theories can also be argued against.

Cultural relativism

Cultural relativism is the belief that a person’s cultural practices should be evaluated through the lens of that person’s culture. These practices also occur when doing business in other countries. For example, midday or napping at work is permitted in countries such as Japan and China (also Italy, Norway, Botswana, and even Silicon Valley) so when evaluating napping policies (through cultural relativism), we should review it from the lens of those cultures – not our own or others (Nishat, 2019).(https://www.openaccessgovernment.org/customs-from-countries/59117/). This would mean that napping in cultures where napping is permitted is not problematic. Similarly, if regulations differ in one part of the world, it might be tempting to default to those regulations, even if accidents are likely or risks are high. This view focuses on the differences between cultures and practices rather than similarities. And it maintains that these practices should be respected.Those who oppose the cultural relativist view would direct us to focus on the similarities to see if the differences are as different as they seem. For example, if we recognize napping as providing employee breaks, we must admit that nearly all organizations allow this and that many governments require it. So, by looking at a broader theme, we can better understand that this difference represents fulfilling the need rather than a denial of the need.

Subjectivism

This view is based on an individual’s view of right and wrong. Under this view, morality is merely any person’s view of what morality means to them. For instance, one person may believe it is wrong to lie, and another may believe it is wrong to lie about big things, but that little white lies are permitted. The strength of this view is that it can help people become more understanding of differences, beliefs, ideas, and cultures. It insists that an open mind be maintained, and judgment withheld.The most challenging part of this view is determining how anyone can be held responsible for what they have done. If a person deems something morally right, then who is another person to object? Yet, we have relationships and interconnections with others that depend on trust and accountability. Without these, imagining moving forward with business ventures or relationships is difficult. After all, if morality is subjective, it can also change. This means if a person changes their view of what is moral, it can significantly impact our interactions with them. We can also change our minds, altering the scenario for others.

Skepticism

A moral skeptic believes we cannot gain knowledge of morality (moral truths, principles, and values cannot be determined). This is evident in our conversations about moral choices. We hesitate to ascribe blame or are too quick to blame. We excuse some behaviors due to circumstances, but not all of them. We see things differently depending on who we disagree with, rendering our views meaningless. If we knew what morality or moral truths were, we would not need to be hesitant or quick to provide exceptions. If this is the case, then morality is not merely subjective. Instead, we have reasons to be skeptical that we can even unpack this topic.We have arrived at the point where there is not much to say or discuss. If skepticism is correct, we cannot even have this conversation and must state that we do not know enough to contribute to the conversation. Yet, our lives and relationships (personal and business) would continue but without any moral claims. While holding morality to a strict understanding of knowledge of morality, it does seem that to navigate this world, we must at least be able to have conversations about responsibility, integrity, fairness, bias, and ethics. But to do this would be to reject skepticism.

Understanding the importance of Ethics in AI

Since this is an ethics book, it seems right to share how or why this information is needed in the work of artificial intelligence. In short, the same people who develop technology, choose which innovations to support, and promote the same are using the processes above to make and support their decisions. These ethical decisions are built into all technology by the nature of their developers and the society they engage with. Whether choosing to develop smart vehicles with autonomous driving capabilities, participating in airport screenings with AI-assisted cameras, or hoping to avoid a speeding ticket via a camera at a stoplight in a local city – the challenge of understanding the impact of choice is required as it always has been with technology.Similarly, the choices between those who use technology and those who develop it are on a continuous collision course with each other. Sometimes the impact is favorable, and the decisions and choices are enmeshed with great support. Other times, the collision is less favorable or even harmful, placing users in opposition to technology and its developers. The dividing line between them is in the ethical decisions and protections afforded by and to both sides.Due to the interwoven nature of combining ethical judgments (good and bad), ethical implications in technology are a nuanced conversation. While many people outside of ethics believe what is ethical is a mere popularity contest, it is instead an understanding of navigating this ethical edge between competing interests, wants, and needs – even when all have strong arguments in their favor. Ethics is no simple coffee chat or tense conversation over the holidays. It is instead a robust interrogation of ideas, an embrace of counterarguments, acceptance of the weaknesses of views held, and still arriving at a decision to be acted upon. It is the work of ethicists trained in philosophy, argument, logic, and humanity.The reason ethics must be consciously addressed in AI technology is because ethics can and has been easily avoided and side-stepped. For instance, an organization may claim to be trustworthy (this is performative speech since the speech is intended to perform the act of generating trust). However, that same company can say they are trustworthy but then make choices that fail to reflect the promise of trust. Saying one thing and doing another is common. Unfortunately, when it occurs with the speed and scale of AI, the problems with doing so are compounded. This can be seen through lawsuits aimed at the largest technology companies: Meta (anti-trust, privacy, children, copyright), Microsoft and Open-AI (copyright, intellectual property), Apple (treatment of developers), Alphabet (copyright, Digital Millenium Copyright Act (DMCA)), account suspensions), Amazon (anti-trust), Samsung (price-fixing). While most of these are related to AI (the exceptions being Apple and Samsung), all involve ethics and technology.

Summary

In this chapter, we have identified how we make moral choices, explored the three primary moral theories, and discussed their objections. We have also discussed the difference between ethics and morality, the moral principles that underpin our choices, and the moral theories that align with them.When confronting ethics in AI, it is important to understand that developers, users, and even venture capitalists will be making judgments about products that incorporate these theories. A founder may be concerned about the utility (greater good and happiness of users or society) but may be in talks with a deontological funding representative. Or a product may be released by a deontological team only to learn that users were seeking utility. There may also be an instance where a developer may wonder if accepting a funding offer would still allow them to be viewed as a good company or organization. Any of these views and those involved can lean toward the three primary views or reject them completely as they make decisions. Where people are involved, mismatched views can lead to challenging relationships, situations, and products or uncomfortable scenarios for everyone.In the next chapter, technology will be introduced to understand its early foundations and begin understanding the practicalities of ethical exploration of technology and AI in later chapters and sections of the book.

Further reading

The following resources have been provided to help you explore this chapter’s content:

https://www.youtube.com/watch?v=1A_CAkYt3GY

https://www.youtube.com/watch?v=-a739VjqdSI

https://www.youtube.com/watch?v=8bIys6JoEDw

www.petersinger.info

https://www.youtube.com/watch?v=PrvtOWEXDIQ

References

Cahn, S. M. (2018). In Exploring philosophy : An Introductory Anthology (pp. 362-373). New York: Oxford University Press.

Green, H. (2016, November 14). YouTube. (Crash Course) Retrieved 10 23, 2023, from https://www.youtube.com/watch?v=8bIys6JoEDw

Nishat. (2019, 2 18). Open Access Government. Retrieved 01 2023, 10, from https://www.openaccessgovernment.org/customs-from-countries/59117/

Seven moral rules found all around the world. (2019). Retrieved October 12, 2023, from https://www.ox.ac.uk/news/2019-02-11-seven-moral-rules-found-all-around-world#:~:text=The%20rules%3A%20help%20your%20family

2 Moving from Ethics to AI Ethics

It isn’t easy to understand the importance of AI ethics if the technology is not understood nor the history it brings – of algorithms, innovation, and ethics. In this chapter, we explore how AI became the generative AI that has become popular and the environment in which it was deployed. Here, we aim to provide you with historical context and a foundational understanding of today’s technology.In this chapter, we’re going to cover the following main topics:

Tracing the evolution of early technology: Developing algorithms

Innovating with early algorithms: From chatbots to social media

Uncovering ethical concerns around gaming

Detecting a new inflection point: Generative AI

Renewing the call for ethics in an era of generative AI, social media, and gaming

Tracing the evolution of early technology: Developing algorithms

It might be tempting to think of inflection points like generative AI or social media as the advent or beginning of AI. Yet, AI did not arrive out of the blue, nor was it unexpected by those in the industry – or those with their finger on the pulse of technological innovation. Instead, our earliest technologies paved the way for the innovations we enjoy today. And it would require radical advancements in hardware, storage, capabilities – and algorithms before AI could be explored with seriousness.The technology age truly began around 1900. It is notable due to the massive size and scale of innovation that followed the turn of the century. While the preceding ages allowed for our creation of tools, electricity, and understanding, the innovations from the 1900s made our modern world possible.

Women in the History of AI

As a book on ethical AI, women are emphasized in its narrative due to their lack of representation in the field. To eliminate them in this text would be to continue disregarding their meaningful contributions (Further reading, Resources 1 and 2).

In the decades between the 1900s and 1945, computers were simply people completing manual computations using tables, differential analyzers, and other detailed information (data). During the World Wars, (human) computers were used to provide the path and trajectory of shells, assisting the military in achieving its goals. Meeting the pressing needs of the military during the world war required innovating this computational process.When federal initiatives must progress quickly, they often turn to higher education and forward-thinking departments where the work is already underway. The appeal to the administration at the institution is federal funding and advancing the work that can then be credited to the institution. This often secures additional funding or future projects for the government. The Moore School of Engineering (at the University of Pennsylvania) had already set up a mechanical computer that could solve problems in minutes – not months. Its funding came from the New Deal under the federal government.In 1946, just a year after the dropping of the atomic bomb, the first digital general-purpose computer was introduced – the ENIAC (Electronic Numerical Integrator and Computer). What had been created was a computer that could accomplish tasks that were too complex or time-consuming for human computers and faster than the mechanical computer. By contrast, this new computer could complete thousands of additions per second using algorithms designed and developed by women already working at the Moore School of Electrical Engineering. It, too, was a federally funded project.Through the use of algorithms, the contribution of ENIAC’s legacy is this whole computerized world and all the technologies that stem from it (E, 2021). Because of the ENIAC, everything from chatbots to generative AI was made possible. It was an inflection point for technology that has since revolutionized our world.

Wars and big science

“The wars were thus responsible for speeding the transformation from “little science,” with research still largely restricted to small-scale efforts by a few isolated scientists, to “big science,” with the emphasis on large research teams sponsored by governments and corporations, working collectively on the development and application of new techniques” (History of technology | Evolution, Ages, & Facts | Britannica, 2023)

It should be mentioned that this process is not without ethical challenges. If an ethicist had been asked, there would have certainly been questions about the process and assisting in the development of weapons. There would have been additional questions about whether a war can be just and whether people who are involved in that unjust war are behaving unethically. Issues of proportionality, harms, suffering, just cause, fairness in war, and many others would be questioned as well.But there are also social issues that should be considered as well. The great challenge of this era was connected to the challenges regarding segregation, discrimination, and civil rights. The unfair irony in fighting a war about unfair treatment of others in another country, while living under inequity is not only profound but an ethical question. One that was responded to through the civil rights movement years later.The political environment under the New Deal as the US recovered from the Great Depression would have also put pressure on the institution to assist the government if asked to do so. Further, the money the Moore School received for the mechanical computer could have applied pressure to the decision to help the military. If that is the case, then we must consider whether it was truly a choice or if it wasn’t. If it was a manipulated choice, then we might not hold them accountable for the harms or deaths the increased accuracy led to.An additional consideration is whether the war was unethical or if taking money to advance the efficacy of killing is ethical. Those questions find themselves rooted in just war theory, under philosophy. And to date, the prevailing view is that there have been no just wars.(Further reading, Resource 3) Still, the institution may have thought that winning the war was the only way to end it, or that their students deserved to be funded. If there was a noble reason, we might excuse their choice. But then we would also have to determine what makes a choice noble.We should certainly ask more questions about these situations as they occur while also challenging the status quo, which may not serve the purpose we hope for. This conversation also serves as a reminder that there are consequences for missing an opportunity to do ethics or to question choices and decisions. While no one can definitively say why UPenn chose to be involved with the military in this instance, we know that its choice to do so materially changed our world.We will now discuss how one innovation after the other led to an era of social media and chatbots that we are in today. We will also discuss ethical considerations leading to this era.

Innovating with early algorithms: From chatbots to social media

We will now discuss a historical timeline of the growth of algorithms that powered chatbots and social media and the ethical considerations around them (Table 2.1). Our timeline will go up to the year 2010; we’ll look at more contemporary innovations and their challenges in future chapters. For now, we need a starting point.

Table 2.1 – Timeline of advancements in chatbots and social media

Twenty years after ENIAC, the first chatbot, ELIZA (1966), was developed. While it used pattern matching and substitution to engage in conversations with users, it also used scripts to predict answers. PARRY (1972) was developed to mimic schizophrenics and attempted to simulate the effects of the disease. Rather than scripts, PARRY used weighted measures and incorporated “assumptions, attributions, and emotional responses” to determine how to respond to prompts (Ina, 2017). When measured against the Turing Test, the program provided better than random accuracy. Later, Jabberwacky (1998) was developed; it intended to simulate human conversation using “contextual pattern matching” (Ina, 2017). Between 1991 and 2010, Dr. Sbaitso (Sound Blaster Artificial Intelligent Text to Speech Operator, 1992), ALICE (1995), and SmarterChild (2001) paved the way for personal assistants through their advanced capabilities in understanding voice and text interactions. Chatbot development after 1991 overlapped with the evolution of social media so the discussion of chatbot history will continue after the introduction of social media.Before the 1990s, though, the world was primarily analog (physical), with people sharing information in person. Photographs and payphones were the norm. Desktop computers were standalone systems unable to share information with another computer or user. However, "On August 6, 1991, without fanfare, British computer scientist Tim Berners-Lee published the first-ever website while working at CERN, the huge particle physics lab (Nix, 2016)." This allowed information sharing to occur between people through technology, and the social media race began.The first social media site, Six Degrees (1997), allowed users to connect with others through the profiles they created and shared connections. Social networks like Myspace followed, reaching 1M users by 2004 (https://ourworldindata.org/rise-of-social-media). From 2004 on, we saw social media grow in popularity through the evolution of Facebook, Reddit, YouTube, and all the other social media platforms that quickly come to mind (LinkedIn, Snap, TikTok, and others) followed Facebook. Facebook, though, marked the point in time when individual social networks became what we understand to be social media today. However, the most significant social media innovation was just on the horizon.People drove social media activity and explored users’ similar ideas, viewpoints, and topics, ultimately establishing groups for further exploration. Leaders and organizers became leading voices in exchanging these ideas in their groups. Soon, leaders became content creators and subject matter experts, with users turning to them for advice.About 2005, developers took notice of this shift to advice-seeking from the previous connection-based interactions and created entire platforms, like Reddit, centered around the sharing of advice. By 2006, the power of groups and leaders led to the inclusion of ads on social media to generate revenue through leaders' recommendations, who now turned into influencers.By 2010, just six years after the advent of social media in 2004, WeChat/Weixen had developed a platform that allowed users to send messages to each other. While WeChat’s success is more than impressive and seen as a close rival of Facebook, its great accomplishment was allowing users to send private messages to other users. This use of conversational technology continues to evolve today. Still, this is not the end of the legacy of social media.In 2010, the same year that WeChat was first released, another innovation related to chatbots occurred. Conversational chatbots using AI, like Apple’s SIRI, launched in 2011, could now understand natural language (the way we talk) aided by voice recognition. Natural language could now be understood and acted upon with a simple “Hey, Siri.” Of course, Google (2012, Google Now/Google Assistant), Microsoft (Cortana, 2014), and Amazon (Alexa, 2014) followed and became SIRI’s competitors. By 2014, the AI race had become mainstream, and the race to find its uses continues today.It should come as no surprise that social media was still thriving as the evolution of chatbots with AI capabilities grew. In 2013, AI and social media converged in the perfect opportunity for innovation. According to the Pew Research Center, in May 2013, 72% of adult online users were using social media (Smith, 2013) (https://www.pewresearch.org/internet/2013/08/05/72-of-online-adults-are-social-networking-site-users/#:~:text=As%20of%20May%202013%2C%20almost). At that time, technology had allowed interactions through direct messaging, yielding a treasure trove of data and information, with AI now capable of filtering that data into usable insights.While recommendations of influencers still had sway, social media platforms could now learn of users’ interests through their activity on sites, through ads, product recommendations, and ideas became easily shared with the right market for them. Experts and leaders were no longer required to present ideas or products. Instead, the AI (algorithm) running in the background on the social media site could recommend ideas, products, and services - and even suggest new thought leaders and content creators.At the time that this technology was evolving, much emphasis was on the capabilities of technology. New things always seem shiny and hold much appeal. That is not to say that ethical concerns were non-existent. But the concerns were more about finding helpful connections rather than harmful ones, avoiding “stalkers and creeps,” and the challenge of being always accessible through email and messages. Few noticed the change from choosing trusted voices to the algorithm’s influence in the process. Fewer still recognized that AI was involved in chatbots until conversations went awry. While not explicitly stated, our focus, so far, has been on adult users who were able to weather the online challenges of social media fairly well.However, this casual view of technology and its harms was not only limited to adults. Children were not left behind. Instead, they had their own relationship with technology: enter the rise of the teen gamer and a formal call for ethics. Let's now move our focus to gaming and the ethical concerns associated with it.

Uncovering ethical concerns around gaming

With the advent of social media and the use of algorithms, another technology (also using algorithms would lead to early calls to consider the ethics of technology. Pong (a digital version of ping pong) was a popular arcade game that captured public attention in 1972. However, by the early 1970s, Magnavox’s Odessey game console would bring arcade games into the home with its version of Table Tennis.By 1975, Home Pong was popularized by Atari, and by 1977, joysticks, cartridges, and color were introduced into video games – and the race to create games that could be played on computers began. And with it, a generation (Gen X – 1965-1980) of computer and video game players who heralded in and adapted to every innovation that has followed.

Let the games begin

A 1982 cover of Time magazine screamed “GRONK! FLASH! ZAP! Video Games are Blitzing the World!” If you turned on the radio that year you’d likely hear “Pac-Man Fever,” a Top 40 hit by Buckner & Garcia. Children begged their parents to buy them an Atari for Christmas or to give them a few quarters to drop in Pac-Man’s coin slot. Hollywood movies like Fast Times at Ridgemont High presented the video arcade as a quintessential teenage hangout. (Magazine, 2017)

For those who remember those early years, the drive to play and be the best at the games was intense (especially when compared to friends). This led to the ongoing desire for more complicated games, gaming paths, characters, and options that extended beyond an A/B choice. These more complicated games required more complicated algorithms, and game developers from Magnavox to PlayStation (and all the others) did not fail to deliver while gaining more dedicated (obsessed) users.With the evolution of video games, the 1980s also brought societal concerns about people’s obsessive behavior—notably the “War on Drugs” President Regan’s administration promoted in the US. While not immediately obvious, concerns about addiction became mainstream alongside social media and video game usage. From the early concerns of addiction like gambling to behavioral concerns, the panic induced by children being “sucked into gaming” and changing was an ongoing conversation. In 1994, the Entertainment Software Rating Board (ERSB) established a voluntary rating system in the US.

A compromise is reached

…After consulting a wide range of child development and academic experts, analyzing other rating systems, and conducting nationwide research with parents. ESRB found that parents wanted a rating system that has both age-based categories and concise and impartial information regarding content. With this philosophy in mind, today the ESRB administers a three-part system that includes Rating Categories, Content Descriptors, and Interactive Elements. (Magazine, 2017)

The next big innovation in video games was Voice over Internet Protocol (VoIP), a technology that allows a person’s voice to be transmitted from one IP address to another. By 1995, chat was established in video games. Early use is attributed to Activision, a video game publisher, though lack of integration with the controller limited its popularity. Widespread use of voice in gaming occurred when Sega built it into the Dreamcast in 1999, allowing users to chat via the browser. With the rising popularity of video games, concerns regarding the dangers of gaming continued at homes and schools, and with ratings in place, games could include any content, with parents responsible for monitoring what games were played by their teens.However, the Columbine Massacre (a school shooting that killed 15 and injured 24) in the US on April 20, 1999, led massive credence to those concerns when two students appeared to reenact a simulation from Doom. The home console was only 25 years old and only a few years older than the shooters. The resulting investigation into the shooting seemed to provide insight into the perceived impact of video games on teens:The Simon Wiesenthal Center, which tracks Internet hate groups, discovered last week in its archives a copy of Harris' website with a version of the bloody shoot-'em-up video game Doom he had customized. In Harris' version there are two shooters, each with extra weapons and unlimited ammunition, and the people they encounter can't fight back. When Harris and Klebold went into Columbine on April 20, says an Internet investigator associated with the Wiesenthal Center, "they were playing out their game in God mode" (Pooley/Littleton, 1999).… What they did wasn't about anger or hate," he says. "It was about them living in the moment, like they were inside a video game." As long as they were rolling with the plan, Brown argues, the slaughter didn't seem real to them. But that explanation absolves the killers too easily: Is it really possible that the flesh and blood of the maimed and dying was no more real to them than pixels on a video monitor? Brown thinks so. "Then they can't get out of the library, and they have a moment of overwhelming remorse," he surmises. "Or maybe one does, while the other is still lost inside the game” (Magazine, 2017).By 2005, such violence and school shootings reached the consciousness of the white suburban middle class and gave rise to moral panic among ordinary people and politicians.

Moral panic

A moral panic occurs when a group or behavior of a group of people is believed to engage in activities that threaten the interests of society. The media often drive these panics through exaggeration of social issues and harms driving fears in society (Further reading, Resource 4).

In an apparent response to the panic, in the US, then-Senator Hillary Clinton, with fellow democrats, introduced the Family Entertainment Protection Act, which sought to levy fines against those who sold M-rated games to minors and would make the ESRB ratings mandatory (Ferguson, 2017). The idea was to limit the most violent games, or those with the most disturbing content, from reaching teens. The bill never made it out of committee (Further reading, Resources 6, 7, and 8).In the same year, 2005, the Game On exhibit at the Tech Museum of Innovation in California included ethical questions about video games, organized by ethical theory (including utilitarianism and virtue ethics, among others) presented by the Makkula Center for Applied Ethics at Santa Clara University (Further reading, Resource 5) (University, n.d.). Their ethical questions included the following (excerpt taken directly from Makkula):

From a Utilitarian Perspective - Some players and developers argue that video games are better at teaching logic and problem-solving skills than many school curriculums. And undeniably, video games bring players pleasure. How would we weigh these benefits against the potential harms that have been attributed to games, such as addiction, gender stereotyping, and the promotion of violence?

From a Rights Perspective [included under utility] - Are video games a form of speech, and if so, do they come under the protection of the right to free speech? Should we try to regulate this "speech" if it degrades women? If it leads to violence? How can we defend the access of adults to whatever forms of speech they choose to hear while simultaneously protecting children from exposure, especially when gaming is such a popular activity for kids? Should it be a crime to sell games with adult content to children? Should content be regulated?

From a Fairness Perspective - Currently, video games appeal overwhelmingly to males. Only 7-8 percent of video game developers are women. Are women being excluded? Is this a problem? In some video games, the only female characters are prostitutes, and the games sometimes encourage killing them. How does this shape the players' views about women? How do questing games portray men, and is that a stereotype?

Common Good Perspective - What effect does video gaming have on the community? At what point-five hours a week? 25 hours a week?-does gaming interfere with people's obligations to their families and communities? Is gaming an asocial activity, or does it involve players in a different kind of community? Can true communities exist online? Do game developers have any obligation to make the on-line experience less addictive?

Virtue Perspective - Understanding that there are only 24 hours a day, how much time should you fill up with video games, and what kind of person will that make you? Is there anything inherently more virtuous about reading than about playing video games? What difference does the content make? Does playing violent video games make you violent? Does playing violent games desensitize you to violence? Let's say the violence does not affect you, but you know that for some subset of the people playing video games, all the gore brings out an inclination to violence-should their access to the games be restricted, and how? Should young children be allowed to play violent games? (University, n.d.)

But the conversation wasn’t over, in 2006, individual states decided to address the challenge of video game content due to the lack of success at the federal level. The final showdown would involve the state of California passing a law that banned the sale of violent video games to anyone under 18 (using pornography limits as a guide). Once the law passed, lawsuits were filed to overturn it, leading to appeals and, ultimately, a decision to be made by the United States Supreme Court. The saga of protecting children was about to take a predictable and unsettling turn.In 2011, after the appeals were launched, the case made it to the US Supreme Court. Ruling on Brown v. Entertainment Merchants Association & Entertainment Software Association they ruled that video games' violence (and other troubling content) was no different than those in art, language, and other creative fields. This gave video games the same protections as artists who paint nudes or music that used foul language and uncomfortable topics. Video game content, created by the developers, were now protected by the First Amendment – but the children weren’t protected at all.From that point on, the overarching theme has been one of “anything goes” as developers and media went all in with “shock and awe” (a military term that refers to an overwhelming use of sudden force) – unimpeded. The result: violent and concerning content permeated all social channels – including social media, chats, DMs, and more. Shooting, suicide, live-stream violence, sexual harassment, stereotypes, bias, racism, hatred, and worse still have safe harbor online. Technology companies also continue to rely heavily on First Amendment protections in defense of a lack of content moderation, suggesting only that parents are the best people to intervene on their child’s behalf.One of the greatest challenges is that harm once online spreads to other people and places, emboldening others to post and share the same content. By the 2020s, online violence and harm had become a global problem. Despite this global concern, moderating or passing (and enforcing) laws against it has proven challenging and largely futile.Of course, the view that parents address content moderation is reasonable only if harm is limited to minor children. Before addressing whether this holds, we must discuss the introduction of AI to the public.

Detecting a new inflection point: Generative AI

At this point, we have discussed the development of algorithms and the different technologies that have embedded them. Algorithms have revolutionized our world, from social media to chatbots to video games. But a technology discussion cannot be complete without discussing the most recent innovation using algorithms – one less than a year old.Open AI, a once-open-source technology company, released a project years in the making – ChatGPT – in beta to be tested by the public. Fortunately, for Open AI, the public was enthralled, much like the teens of the 80s and their video games. Interestingly, few understood that ChatGPT-3 was only a beta test, overlooking the problems and challenges of the latest innovation. But why was this innovation so exciting?ChatGPT is one kind of generative AI that can create images, audio, and text from natural language (language like ours). This technology allowed people without computer programming to use AI to create emails, ask questions, receive answers, and even write resumes and cover letters with simple prompts and background information. And generative technology was not only limited to writing, instead, it was now possible to generate images, audio, video, and other modalities with nothing more than a prompt. A new day in technology had arrived, and users were anxious to begin exploring how generative AI could aid them in their work.With the tremendous growth rate of generative AI, feedback was immense and not without identifying significant problems – of the same kind found in social media. This is because when Chat was developed, the training set for it came from social media sites. After all, the task was to have technology “talk” like we do. So, for ChatGPT to learn how to talk, it needed to be trained in conversations, and the available conversations were those that had taken place online. These could easily be found in public posts, comments, message boards, or any public forum that granted access to their data. This meant the training set used social media posts (like those on Twitter (now X) and Reddit) as training material. So, Chat learns conversational speaking and context from the social content, which has long been a global concern.ChatGPT’s popularity drove innovation and interest in generative AI of all kinds. Other tasks that could now be completed include (but are not limited to) the generation of images from words, simulation of voices, and creation of deepfakes, all while being simple, inexpensive, and easy to do. Yet, each contained the same problematic views, content, and information as social media, and they use training sets from the same sites and companies that compile them.Still, public interest continued, and demand for this technology moved from an open-source AI to closed-source and from beta to invested ($10B by MS) in only a few months. Despite ChatGPT and OpenAI’s sudden and brief entry into the public, the already massive ethical challenges were multiplied extensively through proliferation. The questions introduced by the Makkula Center in 2005 remain relevant today.Now, let us review those questions through the AI lens to identify the problems we must tackle in the subsequent chapters.

Renewing the call for ethics in an era of generative AI, social media, and gaming

As noted in the Uncovering ethical concerns around gaming section of this chapter, the call for ethics in technology began with the concerns of video games and arcades, continued through the Columbine Massacre, and was fully articulated in 2005 by Makkula. It’s been 18 years since Makkula articulated the concerns of generations, and yet all these years later, little progress has been made to address them. In fact, in October 2023, Meta (Facebook) was sued by more than 40 states in the US over concerns that it designed its platform to be addictive while exposing children and others to harmful content (Levinson, 2023).In the same vein, generative AI technology contains bias, stereotypes, gender challenges, hallucinations (made-up information), untruths, violence, and the power to influence choices. This is a direct result of using predictive technology and large data sets, which allow for multiple plausible answers to a single question and include human patterns of bias and harm. Yet, judges are using it in their courtrooms to make decisions regarding sentencing, and an attorney used it to submit a court brief with hallucinated reference cases. Businesses have had content released to the public and their competitors, and privacy policies are being revised to attain user data for training or selling to others to use to forward this technology. Governments and businesses also use this technology despite the concerns and impact on public lives and trajectories. Yet the concerns are familiar and directed toward technologies (video games, social media, chatbots, and AI).So similar are these concerns that plague today’s technology from previous versions that with a simple switch of the words video games to AI, the questions from Makkula in 2005 still stand along with their original concerns. To drive home this point, let’s look at the original wording from Makkula in 2005 and an updated version addressing concerns for AI in Table 2.2:

Then
Now

From a Utilitarian Perspective
Some players and developers argue that video games are better at teaching logic and problem-solving skills than many school curriculums. And undeniably, video games bring players pleasure. How would we weigh these benefits against the potential harms that have been attributed to games, such as addiction, gender stereotyping, and the promotion of violence?
Some users argue that technology (including AI) can better teach logic and problem-solving skills than many school curriculums. But, how would we weigh these benefits against the potential harms that have been attributed to technology , such as addiction, gender stereotyping, and the promotion of violence and harm?

From a Rights Perspective [included under utility]
Are video games a form of speech, and if so, do they come under the protection of the right to free speech? Should we try to regulate this "speech" if it degrades women? If it leads to violence? How can we defend the access of adults to whatever forms of speech they choose to hear while simultaneously protecting children from exposure, especially when gaming is such a popular activity for kids? Should it be a crime to sell games with adult content to children? Should content be regulated?
Is technology a form of speech, and if so, do they come under the protection of the right to free speech? Should we try to regulate this speech if it degrades women? If it leads to violence? How can we defend the access of adults to whatever forms of speech they choose to hear while simultaneously protecting children from exposure, especially when AI is embedded into technology , and it is such a popular activity for kids?

From a Fairness Perspective
Currently, video games appeal overwhelmingly to males. Only 7-8 percent of video game developers are women. Are women being excluded? Is this a problem? In some video games, the only female characters are prostitutes, and the games sometimes encourage killing them. How does this shape the players' views about women? How do questing games portray men, and is that a stereotype?
Only 6-12% of developers and AI researchers are women (Mebourne, 2023). Are women being excluded? Is this a problem? In technology, women are often undervalued or harmed . In modern games, female characters are sexualized , and the games sometimes encourage killing them. How does this shape users’ views of women?

Common Good Perspective
What effect does video gaming have on the community? At what point-five hours a week? 25 hours a week? -does gaming interfere with people's obligations to their families and communities? Is gaming an asocial activity, or does it involve players in a different kind of community? Can true communities exist online? Do game developers have any obligation to make the on-line experience less addictive?
Does technology use interfere with people's obligations to their families and communities? Is the use of technology a social activity, or does it involve players in a different kind of community? Can true communities exist online? Do developers have any obligation to make the on-line experience less addictive?

Virtue Perspective
Understanding that there are only 24 hours a day, how much time should you fill up with video games, and what kind of person will that make you? Is there anything inherently more virtuous about reading than about playing video games? What difference does the content make? Does playing violent video games make you violent? Does playing violent games desensitize you to violence? Let's say the violence does not affect you, but you know that for some subset of the people playing video games, all the gore brings out an inclination to violence-should their access to the games be restricted, and how? Should young children be allowed to play violent games?
Is there anything inherently more virtuous about reading than about using technology ? What difference does the content make? Does using violent technology desensitize you (or a subset of people) to violence and harm? Should harmful technologies be allowed to influence people ?

Table 2.2 – Ethical questions then and now

Scope for Table 2.2

This table updates the questions that Makkula introduced in 2005. Additional questions regarding bias, copyright infringement, training on proprietary data without licensing, and many other present harms will be addressed in future chapters.

In these statements, video games were substituted for technology because, in truth, all technologies contain the same challenges. There is one important distinction: the scale and speed of AI are causing these harms to spread around the globe in a matter of seconds. These capabilities brought not only the benefits of technology but the harms that continue to follow us throughout each advancement we have made.Harmful comments, statements, biases, threats, and worse can spread around the globe in seconds: hackers and those seeking to be disruptive or to challenge development. With innovation comes the benefits of technology and the potential to harm. They are two sides of the technology coin.And in the age of AI, the list of provided concerns can and should be expanded to include far more than what is presented here. That’s for another chapter, for now, it is most important to note that we are revisiting concerns that society has been aware of for more than 40 years.

Summary

At this point, it is fair to say that AI is just one of many in a long string of technologies that carry with it the harms inherent in our society. While we have evolved technology, our actions, comments, and beliefs have changed little since its early advent. While we have become more sophisticated, we still lack basic care for others and their plight. In short, we have become immune to the calls of ethicists and the act of doing ethics with the fate of our families, neighbors, friends, and colleagues as the beneficiaries of our neglectful stance. Unfortunately, the choice to leave ethics for future innovations (or generations) has revealed no such inclination to do so when the future arrives.In the next chapter, we will discuss why it has seemed impossible to do ethics meaningfully.

Further reading

The following resources have been provided to help you explore this chapter’s content.

https://www.womentech.net/en-us/women-technology-statistics

https://www.globalapptesting.com/blog/the-women-who-changed-the-tech-world

https://opiniojuris.org/2022/06/27/just-war-theory-the-only-winner-across-four-grim-conflicts/

https://daily.jstor.org/moral-panics-a-syllabus/

https://www.scu.edu/ethics/

https://www.congress.gov/bill/109th-congress/senate-bill/2126

https://www.visitthecapitol.gov/sites/default/files/documents/resources-and-activities/CVC_HS_ActivitySheets_Committees.pdf

https://www.washingtonpost.com/wp-dyn/content/article/2005/12/16/AR2005121601883.html?itid=lk_inline_manual_5

References

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3 Doing Ethics: Overcoming Objections

Now that we understand how we got here in our relationship with technology, we must decide what to do now. Unfortunately, getting started is one of the most challenging parts of doing ethics. And there are many reasons that can be used to avoid doing the work. Yet, the objections to moving forward are not insurmountable once they are better understood and more fully explained. That is the point of this chapter and the foundation on which our future work will be based.This chapter aims to address the many objections to doing ethics. It will also explain why this work is difficult, why it may be tempting to avoid, and how we find a way past the problems to begin the work of “doing ethics.”In this chapter, we’re going to cover the following main topics and objections:

Overcoming objections to doing ethics

Finding Commonality in Conflicting Ideas and Priorities

Finding Practicality in Advice and Guidance

Overcoming Perfection and Ideal Theories in Ethics

Challenging Frameworks

Doing Ethics

Overcoming objections to doing ethics

In philosophy, overcoming objections means addressing head-first criticisms against a viewpoint or position. In this instance, the argument is that we must do the important work of ethics. Now, the process of overcoming objections to that view can begin. To start, we must identify the objections to doing ethics and do our best to try to understand them. To do this, we must see the objection as worthy and valid and see the objection through a position of generosity, which means listening with an open mind, considering that we may have made a mistake before responding, and taking to heart that the other person may be the correct one. Only then can we work on constructing a response. Responses often include adding nuance, clarification, details, or missing facts while respecting the objection and the objector. The benefit of this process is that it helps to strengthen the original argument and to make it better able to withstand criticism. Usually, this is a back-and-forth dialogue between those who disagree. However, when it is in written form, critique often takes place during review or even after it has been published.Remember, focusing on only a few objections means that other objections may be left out, making those who disagree with you turn to new ideas to maintain their position. This means that there will be new objections to overcome. So, the process of overcoming objections is iterative.A final note about overcoming objections that must be mentioned is that the most essential part of this process is to sincerely consider that your view may be wrong – not theirs. This is why viewing opposing arguments from a position of generosity and an open mind is essential. Only by fully understanding their argument and exploring its strengths can you understand how you might explain to them why yours is the stronger idea. You cannot argue against something you do not understand or fully explore. Once you understand the opposing side, you can determine which position you’ll take and better understand how to defend it.We will first talk about how to find an intersection in conflicting ideas and prioritize ethics.

Finding Commonality in Conflicting Ideas and Priorities in Ethics

One of the first challenges that comes up when discussing ethics is a lack of commonality between ethical concepts, ideas, and priorities. For example, trust is a topic that most are familiar with and understand personally. Because of this personal nature and their personal beliefs, many believe that ethics seems to be a matter of personal preference. They say, “I feel I can trust a person when they….” Individuals also understand that different people can end this sentence differently. This individualistic view often results in a narrower view of ethics focused on difference rather than commonality.

Individualism

The act of working alone or of viewing individual needs over collective interest.

Individualism is not only connected to ideas that people hold about what is trustworthy, but they also recognize that what is very important to one person may be less important to another. In other words, we recognize ethical terms and prioritize them in order of their priority to ourselves. This individualistic view poses unique challenges when explored through our perception of ethics as it relates to AI.

Ideas

Ideas are meant to describe thoughts that we have about certain terms or concepts. Some of these concepts in technology are ethical, including trust, protection, and safety. To begin, let’s discuss safety. It should be familiar to recognize that some people are less risk-averse than others, indicating their preference for what feels safe. Similarly, with honesty, what one person considers dishonest and a reason to withhold trust, another may believe that situation to be nothing more than a harmless white lie keeping trust intact. Lastly, what makes someone feel protected can be different for many people. Some people are willing to walk to the edge of a cliff without a barrier, and others might prefer not to leave their vehicles.When applying these concepts to technology, there seem to be too many conflicting preferences and thoughts on the matter to find a “real” answer. Let’s consider three hypothetical people tackling the idea of safety. Let’s consider that Sally’s preference regarding safety (or any of the concepts we’ve mentioned) is rejected by Mark. Meanwhile, it can only follow that Mark rejects Sally’s conception of safety. And imagine that Sally or Mark does not desire Jason’s idea of safety. Jason rejects both of their conceptions. Figure 3.1. The challenge of finding a middle ground seems next to impossible. By extension, creating policies and preferences with such differences is also a challenge since many will be disappointed regardless of what decision is made.

Figure 3.1 – Demonstrating Lack of Agreement

The previous paragraph briefly mentioned our hypothetical Jason’s idea of safety. The subtle change from discussing safety to Jason’s idea of safety is significant. Safety as a definition means to be protected, but here we’re focused on what makes Jason feel safe.This reveals that the challenge of drawing conclusions about these concepts hinges on what people believe or their ideas about them. And if each person has their own ideas about each ethical term or principle that inform their reaction to circumstances and there are roughly 7.5 billion people in the world – that’s a lot of conflicting ideas and too many to consider – let alone act upon or use to create policies thoughtfully. And yet, these concepts are meant to become part of the ethical frameworks that guide AI. But how?

Ethical Framework

A structured set of rules or guides that provide a systematic approach to ethical problem-solving.

Suppose that instead of seeing individuals, we saw them as groups. Let’s aim to create 3 large groups to make things simple (and manageable) at this point.

We’ll call the first group the Mavericks; they are the risk-takers. These are people who look before they leap, “go fast and break things,” or consider the risk worth the reward (without giving the risk much consideration). For example, they may bungee jump for the first time with a company they are unfamiliar with beyond reviews, they may find seatbelts unnecessary or may believe that protections are largely overreaching.

Then, let’s create a second group for very risk-averse people; let’s call them the Cautioners. Cautioners are dotting their I’s and crossing their T’s. They leave little to chance and err on the side of caution at every turn. They have lists, plans, and contingency plans. And there is no way they are bungee jumping – and if for some reason they decide to attempt it they will vet the company, the plane, the person who pack their gear, their safety protections, reviews, and will want documentation to prove it – and they will not agree to be the first jump of the day. After all that research, they may not even go at all.

Lastly, we’ll create a list for those who are in between – they are neither Mavericks nor Cautioners and instead are the Centers. These people focus on a pragmatic approach to risk. They will “kick the tires” but with strong assurance they are likely to take the leap. They may also have a plan B, but not a contingency for excessive potential outcomes. They are willing to take calculated risks, but they do not need to be an engineer. This is the middle position, much like the golden mean of virtue ethics. Figure 3.2.

While you may not know everyone’s personal view on safety, you can sort through this challenge using categories.We are not looking to create overlap between the groups or a Venn diagram; instead, think of these as containers or buckets – separate from each other. Now imagine a fast sorting of people; you only have three choices, and each person can only be placed in a single category. (The Venn-like diagram can come later and allow more nuance for this process, but the idea here is a starting point, and a simpler starting point is best.)

Figure 3.2 – Sorting Method by Risk

No two people will be identical, but there can still be a way to determine who you have the most in common with. Even now, if challenged to choose one of the buckets above for yourselves, you could sort yourselves into a group without introducing other choices. (Some wouldn’t like it, but that doesn’t mean that they couldn’t choose one.)It should be important to note that rather than looking for commonality between those who disagree, we’re finding commonality within each group. So, the cautioners are united in their caution, the Mavericks by their risk-taking, and the Centers by their middle-ground approach to risk. We do not need to find a commonality between Cautioners and Mavericks – or any combination of Jason, Sally, and Mark. Instead, we need to recognize who is most like Mark, most like Sally, and most like Jason. That gets us to a starting point (of course, more nuance is needed, and in time, we’ll get there).

Principle of Commonality

Seeking to look for commonality rather than difference when confronted with an enormous number of disparate ideas or preferences.

To move forward with doing ethics (which involves and is focused on ethical concepts like these), instead of identifying differences, it would be wise to look for commonality. In fact, finding commonality is essential to moving forward with this work. Of course, there will be a time to address differences, but it should not be the first step nor used to avoid this work.

Priorities

Now, we can see issues related to trust broken into categories: those who are willing to take chances, those who wish to see caution, and those who are in the center; we find another challenge: determining priorities. While it is one thing to understand what trust means to us, determining whether to prioritize safety over trust or trust over safety is another question altogether. To determine our priorities, we must first have some basic ethical concepts to consider and weigh against the others. In AI ethics, you’ll see terms like those mentioned previously, such as trust and safety, but you’ll also hear about rights protections, doing no harm, doing good (beneficence), and bias. But how can we know which of these should be our first priority or our last?While no one truly knows how many ethical frameworks are being implemented today, we know that individual organizations are creating their own frameworks for implementing AI at their organizations. So, once again, a majority solution does not seem likely or within reach – there will be differences. Unfortunately, a common view is that if there are many solutions, there are none. It seems AI and organizations could succumb to this view – or that relying on difference again allows for the derailment of ethical AI. But this is misleading. Are we certain that we cannot find something to use as a guide to determine our priorities?Of course, you may have already guessed that commonality can also help us with this challenge. Of the many frameworks, there is commonality among them. So, by looking for commonality, we can find the topics or themes that have resonated with others to give us a starting point. Fortunately, researchers have begun doing this work, and primary analysis of 84 frameworks has revealed commonalities among them (https://arxiv.org/ftp/arxiv/papers/1906/1906.11668.pdf ) Jobin et al., pp. 7-10). While no specific idea or ethical principle was in all the frameworks, the following principles were noted in most of them (73-47 of the evaluated frameworks): transparency, justice and fairness, non-maleficence, responsibility, and privacy. While no specific principle was identified, commonality was still able to be identified and can serve as a foundation to begin ethical evaluations.Yet, we’re still at a loss for how to prioritize those. The decision to consider any of these 5 as equal in priority doesn’t seem to make sense, and merely relying on commonality is a challenge, too. What if your organization is heavily regulated? What if your industry is high-risk? The answer to this dilemma is a matter of triage.

Triage in AI Ethics

The act of prioritizing ethical concerns and principles is determined by the threat of ignoring them on persons, places, the environment, organizations, and larger society.

As you are likely aware, triage is a medical term that allows doctors or emergency staff to determine their priorities. This is usually based on a patient’s risk for negative outcomes, death being the primary driver. Using this as an analogy, we can begin to see how triage can help us prioritize the risks to an organization by AI. For example, if you are heavily regulated regarding privacy, then privacy is likely to be higher on your list of priorities. If you are working with technology that can affect the outcome of people’s lives, then rights protections would fall higher on your list of priorities. Here, the threat to your organization drives your priorities. This makes the choices more straightforward and clearer when they previously may have seemed unclear.For those familiar with engineering this practice may have correlations to on-call shifts where incidents are responded to in the moment, but determining the severity of the issue and the appropriate response is needed. In engineering the idea is to minimize the impact of the issue and to implement a fix if needed. Ethics in this instance can help identify and prioritize which issues need attention first and which may be moved down on the list of priorities.One caveat that is worthy of mentioning, regardless of the need for triage, any situation or circumstance that requires a solution is only bumped down on the priorities list – not removed. Exercise caution and avoid the temptation to remove a task due to difficulty.The concept of triage, pr and on-call work also fits well to the guidance of the Eisenhower Matrix:

Do tasks that are urgent and have significant consequences.

Schedule tasks that are important for success but can be delayed.

Delegate tasks to those better suited to tackle them.

Remove/Delete tasks that are redundant, unnecessary, or distract from the work that is required.

Finding Practicality in Advice and Guidance

It can be tempting to believe that ethical advice and guidance lacks the practicality that is needed to support AI innovation. This is to misunderstand or make assumptions about the contributions of AI ethicists and the work of ethics.challenge to beginning the work of doing ethics is the claim that little of the advice that is received is practical. This view is supported by the many principles, terms, definitions, and disagreements that have come from suggestions. For example, the definition of trust may be interpreted, changed, nuanced, or revised. And in some cases, trust can mean more than one thing. When a technologist talks about trust, they often talk about an algorithm that performs as programmed, and when users discuss it, they are considering whether they should put trust in the app or program they are using. Yet few slow down to realize this challenge or take the time to explain what kind of trust is on offer or is claimed.This challenge of language, terms, and definitions becomes even more problematic when advice is offered under the standard method of frameworks. While a framework appears to be a wonderful tool, many organizational leaders and some of the most tech-savvy individuals see only a list of important terms but no way to make them actionable or to apply them. This often leaves those attempting to tackle ethics and technology with the feeling of, “Now what”? With no one available to answer that question.Fortunately, this challenge has more to do with failing to “say the quiet part out loud” – a phrase that has become a favorite since beginning this work. Saying the quiet part out loud often means saying what no one else will or saying something that was missed by others. So, what is the quiet part that hasn’t been said in this instance? Imagine that a person asks if you have made a revision to a project, you understand that they are really asking when they will see the changes. Regarding frameworks, their creators have largely left the quiet part to the implementers, providing only terms and definitions – and no guidance on using them to do the work. It is the quiet part when doing ethics, that often matters most. Frameworks can be actionable and made practical. Terms and definitions can be made clear and explained to others, so each understands how they are seen by different roles, through different tasks, and by leadership. But this requires understanding where the discussion has gone off course. Technologists, AI ethicists, and users must begin to speak the same language and say their quiet parts out loud to facilitate this process. Each speaking to another but misunderstanding the others or being unwilling to leave the silos of our expertise to see things another way is part of the problem. There is a huge misunderstanding by technologists and developers about what ethicists actually do, and there are misunderstandings by users about what developers and technologists are creating and how ethicists can help. Let alone the host of others involved in this work. Talking past each other helps no one, progress is in the unsaid clarifications that have not been provided. This is a watershed moment, and it is time those involved with AI created and fostered strong non-adversarial relationships with the many people working in the field. This is not a reason to avoid ethics but rather a reason to do technology in a new way that merges ethics, technology, leadership, regulators, developers, and users (all those involved) working together toward a positive end. And that is doing AI ethics.

Preferences Not Solutions

Another practical challenge is that ethics does not work as a practical solution to anything. Instead, it’s merely people's preferences. But this also lacks an important consideration: ethics is the foundation of law. Consider reduced speed zones near schools or important gathering spaces. Why are the reduced speeds required in those spaces? The straightforward answer is that someone noticed that fast-moving cars were dangerous in those locations. Then, they noticed that the danger was not an aberration or one-off circumstance but was instead a continuous threat. Finally, unofficial signs or crossing guards might be placed, hoping that drivers would reduce their speed. Whichever intervention was used, its success (warnings worked) or even the lack of success (still speeding) could lead to an official reduced speed sign being placed. But this is predicated on someone noticing a problem and intervening, the intervention being practical.In AI ethics, the same process exists. A problem is noted, and a solution is sought. Since the problem is tangible, the solution will also serve a practical purpose. This means that ethics is not some impractical attempt to address the impossible but rather a method to solve tangible problems and address them. In fact, objectives and key results (OKRs) and Specific, Measurable, Achievable, Relevant, and Time-Based (SMART) goals can be used in concert with ethical frameworks to provide tangible and measurable actions motivated by ethical concerns. This will be discussed more in future chapters, but for now, know that these processes will assist you in your ethical work. We often do not need to reinvent the wheel but use the knowledge we have to better serve our needs.

The Role of Ethicists

A final practical challenge of ethics work is determining the right placement within an organization for an ethicist. Who will they report to, what department will they belong to, and what will they do all day? Since ethicists are neither lawyers, HR specialists, nor developers who code, it might be tempting to think that finding someone with the above skills is the better choice and easier fit. Again, this is to misunderstand an ethicist's purpose and value to organizations.First, the study of ethics falls under philosophy. Philosophy is distinct from the social sciences because of its adherence to logic as foundational (not coding or law). Logic, as the underpinning of philosophical inquiry, also means that it underpins ethics. This means that applied ethicists (distinct from theoretical ethicists) do not merely want to find an answer to a problem; they seek the right answer based on evidence and reason (logic), allowing them to provide strong justifications for their guidance. These philosophers are not theorists, though they are well-versed in theory. Instead, they want to see their solutions used in the world.Through this foundation, the applied ethicist’s problem-solving and fact-finding mission is closer to that of a lawyer who must know and understand the truth of a situation to assist their client. These ethicists are working on finding solutions to real-world problems and dilemmas. In fact, philosophers have a 75% admission rate to law school – a higher rate than any other major (https://nationaljurist.com/prelaw/classics-philosophy-majors-do-best-when-it-comes-getting-law-school/). When you retain a philosopher’s help, you engage with a critical thinker and meet a skilled problem solver – but without a law degree. It seems right to mention that developers, technologists, lawyers, and HR can be ethics-informed, but being an ethicist is a unique skill set and training that doesn’t exist outside philosophical training.Because of their drive to be compelled by facts and logic, ethicists make expert policy specialists who easily understand the positioning of legal recommendations, consequences, and impact in the world and on people. They are especially skilled at working in a lawless environment where regulations and policies are questioned because they do not rely on laws to do their work. Their natural working environment is exactly like the one in which AI exists today: complicated, lawless, ambiguous, and with many problems to solve.Yet, positioning ethicists within an organization is also an objection to fully embracing AI ethics. With the overlap between logic and problem-solving, an ethicist might be part of an ethics, legal, or technology team within a larger organization. An ethicist might be a board advisor, special advisor, director, or vice president at a small business. The goal would be to place them in roles with influence and adjacent to where decisions are being made. In a heavily regulated industry, annexing them with legal may be a strategic choice. If the industry is customer-facing, they should be positioned to assist HR but aligned with legal. For those dealing with cutting-edge technology, an ethicist should be positioned to assist both legally and with technology.Make no mistake: Applied ethicists are not attorneys, developers, or HR specialists, but they are uniquely qualified to address AI innovations. Similarly, developers, HR specialists, and attorneys do not have the skillset of an ethicist. The roles are not interchangeable but have tremendous value (Further reading, Resources 1, 2, and 3).

Overcoming Perfection and Ideal Theories in Ethics

The goals of perfection and ideals have often hindered applied ethics (ethics in the world). This is because they are unattainable. For many the desire to do things perfectly is a challenge that must be overcome. Voltaire once said that “perfection is the enemy of the good.” And it is the good that we seek when engaging with ethics. Rather than perfect work we would be better served by understanding what perfection might be while aiming for excellence in our work today.Let’s direct our attention to the challenge of perfection in AI ethics. Many believe that since we cannot master or perfect – or guarantee perfection – in AI ethics, we might not consider engaging with it at all. Again, the default answer to this is to wait for regulation – and while it’s coming, it’s not here now, and many situations cannot or will not be addressed by them. And yet, it is true that ethics is unlikely to make things perfect now or in the future. There are too many variables, more innovations to follow, bad actors, and a host of other challenges awaiting us in the future. Failure to engage in this work does not prevent or allow us to avoid these challenges. They will still appear and make themselves known worldwide through publicity, lawsuits, loss of market share, reputational hits, or worse.So, while ethicists cannot guarantee perfection (and no one can), they are able to assist organizations and users in adopting AI and mitigating the damage it can cause. They are also more likely to benefit you through publicity, protecting your reputation, and avoiding lawsuits – essentially the opposite of everything listed above. While there are no magic wands to prevent all the bad, it still seems that seeking the good is a better idea than avoiding it. And your attorneys will thank you for helping them make an argument on your behalf if something does go wrong.After all, your statement to your attorney in case of a public mistake or problem would look like this:

“Our actions conformed to all applicable laws.”

“There are no laws governing this; our actions conformed to all applicable laws.”

“We look forward to a time when laws are enacted the provide guidance in these circumstances.”

Or it could look like the following statement:

“Unfortunately, a situation occurred that no one anticipated, but we are committed to doing what is needed to remedy this – and to continue to make the best choices possible, to find the best answers, and adhere to ethical best practices.”

While an attorney would have to vet and improve these statements, it seems that in the absence of violating laws, the priority would be to care for those impacted and a nod to ethics. The last statement is the only one that acknowledges this.Unfortunately, the statement often relied upon is the first one. Doubly unfortunate is that it is the one customer cares about least. The fact that you made a choice you were sure you couldn’t be sued over offers nothing to your customers or users and resonates as self-protection or self-serving. The second statement fares only slightly better since it focuses on the laws that weren’t broken, leading to the perception that your interests trump theirs. And softening it by promising to follow future regulations also hints that you will continue as you have until new laws are passed. Again, these offer nothing to those you serve. While doing AI ethics is challenging, bypassing it because it cannot be perfect and offers little to organizations, customers, users, or the greater public. And they know that, too.

Ideal Theory

On the other side of perfection is the concept of AI ethics as an ideal theory. To explain this objection to engaging in AI ethics, we must first explain what ideal theories are in philosophy. In this instance, an ideal theory is a certain kind of perfect world to have as a goal. This means that ideal theories are not able to be realized but instead can be used to identify where the challenges are and the problems and harms that need to be resolved or improved.

Ideal Theory

An ideal theory is meant to identify problems in an existing situation or circumstance by identifying the ideal situation or circumstance, revealing the true nature of the challenges and their potential solution. The ideal theory is a goal or aim that directs and informs the needed changes.

In AI ethics, the challenge is analogous. Some believe ethical technology is impossible since technology makes mistakes and cannot be perfect. After all, there will always be bad actors, changes in the environment, future innovations with glitches, etc. The general idea is that since we cannot correct everything and we are chasing the impossible, it is pointless to begin the work. This can be tempting to believe, and it is highly likely that ethicists have also confronted this thought. After all, ethicists have been laid off en masse at certain organizations, and there is much pushback against their work. For every problem solved, fifty to thousands more appear.While ethicists have learned to overcome the challenges of their field. Others use this challenge to avoid the work of doing ethics. Here, as with perfection, failure to attain an ideal has led to some abandoning the work involved in improvement. Yet, again, this abandonment is unwise since the alternative is to accept no improvement in the state of technology’s challenges and problems. It means to accept a world unimproved and not bettered even when better is possible. It is a mistake to focus on an ideal when any improvement beyond the now is still an improvement, and settling for less can lead to more harm.Ethics is not an easy path, even for the ethicist. But to deem it unworthy of exploration or to do the work is counter to the best interests of everyone and the organizations whose ability to thrive depends on their relationships with people outside of their offices and structure. AI has a global impact, and its consequences are felt around the globe. Surely, the world deserves the effort and investment to do what we can while looking for ways to do more.In parenting, it is often said that when you know better, you will do better. An argument that requires ideals and perfection is akin to saying that knowing better should lead to no change or improvement.

Challenging Frameworks

We have already explored the objections to determining the ethical principles that fit frameworks and the difficulty in arriving at a practical or recommended action from merely a principle. But there are other objections too.

Cultural Relativism

When evaluating a principle for a framework, the culture of the entity evaluating it will make a value judgment about it (determining if it is good or bad or how it should be perceived). However, what is ethically acceptable in one culture may be rejected in another. This challenge is especially relevant to AI since it can be deployed globally. Here, commonality can also assist this process through popularity or acceptance but through an evaluation of underlying principles that reveal the reasons why the challenge exists. For example, European nations have a different ethic of care embedded in society than the United States. This does not mean the US is uncaring or the EU is overinvested in care. Instead, this review reveals that care matters but is demonstrated differently.

Incomplete and Rigid Frameworks

It can also be said that frameworks can also be both incomplete and rigid. This is because frameworks can appear to leave important considerations out or only remain fixed on a few main ideas. For those looking for differences, a lot of information would appear to be missed and left out altogether. This does not need to be the case. Instead, frameworks can be expanded to include new priorities or new information. Here, the challenge is to view applied ethics as responsive to changing dynamics and innovation. Additionally, while a line in the sand is needed to begin work and to make progress, regular reviews allow for expansion and the flexibility that we just mentioned. In a society that is not static, with technology that is not static, there is no reason that ethical guidance should be static, too. Still, just as a product launch has to occur at some point, there must be a moment for ethics work to begin. Review, refinement, and adaptation are required in AI ethics and technology.

Bias in Frameworks

Just as bias exists in our society and all people within society, bias is also a challenge for ethicists. As a result, it is possible for biases to creep into frameworks. Ethicists are not perfect or some unfailing examples of moral good. Instead, they are fallible and susceptible to cultural ideas and their own perceptions. They do not somehow get a pass from their own humanity or weaknesses. Still, ethicists are trained to root out their own preconceived ideas, to challenge their thoughts, and to not accept weak answers even in defense of their own views. Self-reflection is required for all ethicists to do their work and to ensure that if there is alignment in their own views to a recommendation, they have examined the possibility that bias is steering them.It is also possible that ethicists could be biased towards ethical theories or principles. This could find its way into frameworks, making them less about the work to be done and more about the views of the philosopher. The degree of self-reflection and transparency that are required to do this work is why philosophical training should be required for those leading ethical AI initiatives. If a different lead is chosen, the likelihood of ethical initiatives reflecting a leader’s views rather than an impartial reflection of what’s needed greatly increases.Let’s move on to doing ethics next.

Doing Ethics

In this chapter, we have addressed the many reasons that are given for not engaging in ethical work. But more than a reason not to do ethics, it is important to consider if there are reasons or a good argument to do ethics. After all, saying a person shouldn’t do one thing isn’t a good reason for why they should do another. In other words, a no to one idea doesn’t immediately lead to a yes for the opposite. Instead, the answer to why you should do ethics is quite different.To do ethics is to recognize our troubled world includes traumatized and harmed people who should not be made worse by our efforts or innovations. The motivation to do ethics is a choice between futures – one of optimism and one of harm.The future of harm involves staying the course. It is a world full of bias, harm, stereotypes, and lost opportunities for everyone. It’s a world where we become unable to fully engage with others and where our technology fails to understand our challenges. It’s a world where chatbots and algorithms make choices as though they are neutral in a world that has no neutrality or objectivity. Explanations of the harm default to legal requirements and a demand for better regulation that cannot be passed nor agreed upon. Technology is developed based on profit rather than need, and the initiatives that can help the world fall to the wayside under a profit model or are left to philanthropy. That world looks a lot like this one, but worse.There is another possible future. It’s not the best of all possible worlds, but it's improving daily. Bias, harm, and stereotypes are addressed and mediated through technology, self-awareness, and self-improvement. More opportunities for us are made available and possible through innovation. We are realizing, again, the importance of engaging with each other and recognizing just how much (and how little) our technology understands our world. We admit that even technology’s choices are ours – coded as capabilities to help us. Explanations of harm involve accountability and responsibility while maintaining profit along with the protection of people and our world. Regulations are valued for what they offer, and ethics is recognized for its ability to fill in the gaps as technology advances. Technology emphasizes the world's needs and profit, noting that a failure to address needs leaves profit in doubt. Philanthropy, profit, and innovation are partners driving a better world – and people are made better for it.These different worlds are examples of ideal theory since we can clearly see what is wrong in society and its relationship to technology, and by extension, we understand what should be made better.

Broken Mirror Theory

But there is another theory that is equally helpful to doing ethics: broken mirror theory. This theory states that technology, data, and societal challenges provide a true reflection of society but that our temptation will be to clean the data or undertake performative actions (thereby improving our reflection) while avoiding the societal work needed to prevent them.In other words, broken mirror theory is another way to avoid doing ethics, but it also provides insight into what we must fix in ourselves, not just our technology. This is because our technology reflects our unconscious biases, our disregard for others and the environment, our failure to engage with the care or support of developing nations, our hatred, our anger, and our frustrations. Our data, technology (such as generative AI’s output), and how we treat each other (which eventually ends up in our data) all make clear that a needed component of this is our own change and development. AI is not only a watershed moment for tech but also one for us.A necessary component of ethical AI is training and educating users, developers, deployers, organizations, and all who interact with or create our technology. Doing ethics then will involve all of us as a society meeting this moment as well.

Broken Mirror Theory

Technology, data, and societal challenges provide a true reflection of society, but our temptation will be to clean the data or undertake performative actions (thereby improving our reflection) while avoiding the societal work needed to prevent them.

Unfortunately, the tendency is to bypass this work through another method, and that is through washing. Washing is a concept where organizations and people hope to gain positive attention by making claims about their ethical initiatives that are not supported by actions or facts. This process has been used in ethics, DEI, work from home, and many other initiatives that have proven difficult to do without the assistance of ethicists.In AI ethics, the problem is more challenging when the most pervasive example of ethics-washing is the hiring and then quiet firing of entire AI ethics departments. Or dispersing ethical voices across an organization preventing collaboration or raising of challenges. This is occurring at some of the largest technology firms including Microsoft, Meta, Twitter, Google, and Amazon. Apple so far has fared rather well but is only new to embracing AI. Overall, in tech, the unofficial motto is to cheer ethics in AI while removing teams or collaborative efforts specifically tasked with ethical work.And what of AI companies? Anthropic was supposed to be one of the good AI companies, focusing on ethics. And it, too, fell to the pressure of the tech industry and is in the process of fighting AI regulation, has financial ties to Google and Amazon, and is accused of mass data scraping. Competition and a drive for profit has even pushed this “good one” to teeter or cross the line of the good into the not good. Meanwhile, OpenAI disbanded its AI risk team with leadership defecting to other organizations.Yet each company mentioned still relies on their claims of responsible AI through trust, safety, risk mediation, and ethics. Even as all have struggled to provide with any consistency the good, ethical, innovation and oversight they have promised.

Ethics Washing

It is a term used by organizations and people to describe the practice of misrepresenting their ethical commitments and social responsibility to be more positive than they are to gain trust.

This avoidance, now the status quo at many organizations, is also a choice between the two worlds first discussed. Some resist a world where DEI, the environment, and social issues bring about change. However, change has already arrived through younger generations, technology, and potential harms that are waiting for us. If there were one situation or circumstance that might impede progress on AI ethics, it is that we are working on engaging ethics in a world and industry that has not yet fully embraced it.In addition to ethics-washing in general, it can apply to specific tasks in AI such as collecting, evaluating, and telling the story of data. Each of these can be flawed or merely influenced by deeply held ideas (biases both positive and negative). Even where to source data are not neutral as certain resources may be favored over others. Finally, the story the data tells can be influenced by needs, preferences, and biases. And each of these influences may be tied to data analysts but also the organization or interests that use them. The interesting thing about data is how much of the process is subject to narrowing choices, decision-making, and biases entrenched in our world.There is always a choice to do ethics, to avoid it, or to question its worth. And with choices come their corresponding consequences, benefits, risks, and responsibility.

Summary

The complicated nature of doing ethics should now be clear. Those new to philosophy may find themselves feeling stressed and overwhelmed by the path ahead. Others may be excited to begin. Either or any reaction to the insights provided here is to be expected. If ethics were meant for everyone, there would be far more people majoring in the subject. The good news is that there are experts who can make this process less intimidating, and there are ethics-informed voices that can make even the expert insight better. Notice easiness was not mentioned because this work is difficult. But it remains worthy of our attention and efforts. And while there are arguments that seem reasonable to dissuade us from the work at hand, they can be challenged and overcome.

Further reading

The following resources have been provided to help you explore this chapter’s content:

The Practical Value of Studying Philosophy: https://www.montclair.edu/philosophy/2023/09/01/the-practical-value-of-studying-philosophy/

The Numbers Game: https://www.apaonline.org/members/group_content_view.asp?group=110435&id=918649

The Philosophy B.A. Checklist: https://www.umsl.edu/~philo/files/pdfs/checklist.pdf

References

Cahn, S. M. (2018). In Exploring philosophy : An Introductory Anthology (pp. 362-373). New York: Oxford University Press.

Green, H. (2016, November 14). YouTube. (Crash Course) Retrieved 10 23, 2023, from https://www.youtube.com/watch?v=8bIys6JoEDw

Nishat. (2019, 2 18). Open Access Government. Retrieved 01 2023, 10, from https://www.openaccessgovernment.org/customs-from-countries/59117/

Seven moral rules found all around the world. (2019). Retrieved October 12, 2023, from https://www.ox.ac.uk/news/2019-02-11-seven-moral-rules-found-all-around-world#:~:text=The%20rules%3A%20help%20your%20family