The Ethics Blog

A blog from the Centre for Research Ethics & Bioethics (CRB)

Tag: robotics

Images of good and evil artificial intelligence

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15 February, 2022 / / 0 Comments

As Michele Farisco has pointed out on this blog, artificial intelligence (AI) often serves as a projection screen for our self-images as human beings. Sometimes also as a projection screen for our images of good and evil, as you will soon see.

In AI and robotics, autonomy is often sought in the sense that the artificial intelligence should be able to perform its tasks optimally without human guidance. Like a self-driving car, which safely takes you to your destination without you having to steer, accelerate or brake. Another form of autonomy that is often sought is that artificial intelligence should be self-learning and thus be able to improve itself and become more powerful without human guidance.

Philosophers have discussed whether AI can be autonomous even in another sense, which is associated with human reason. According to this picture, we can as autonomous human beings examine our final goals in life and revise them if we deem that new knowledge about the world motivates it. Some philosophers believe that AI cannot do this, because the final goal, or utility function, would make it irrational to change the goal. The goal is fixed. The idea of such stubbornly goal-oriented AI can evoke worrying images of evil AI running amok among us. But the idea can also evoke reassuring images of good AI that reliably supports us.

Worried philosophers have imagined an AI that has the ultimate goal of making ordinary paper clips. This AI is assumed to be self-improving. It is therefore becoming increasingly intelligent and powerful when it comes to its goal of manufacturing paper clips. When the raw materials run out, it learns new ways to turn the earth’s resources into paper clips, and when humans try to prevent it from destroying the planet, it learns to destroy humanity. When the planet is wiped out, it travels into space and turns the universe into paper clips.

Philosophers who issue warnings about “evil” super-intelligent AI also express hopes for “good” super-intelligent AI. Suppose we could give self-improving AI the goal of serving humanity. Without getting tired, it would develop increasingly intelligent and powerful ways of serving us, until the end of time. Unlike the god of religion, this artificial superintelligence would hear our prayers and take ever-smarter action to help us. It would probably sooner or later learn to prevent earthquakes and our climate problems would soon be gone. No theodicy in the world could undermine our faith in this artificial god, whose power to protect us from evil is ever-increasing. Of course, it is unclear how the goal of serving humanity can be defined. But given the opportunity to finally secure the future of humanity, some hopeful philosophers believe that the development of human-friendly self-improving AI should be one of the most essential tasks of our time.

I read all this in a well-written article by Wolfhart Totschnig, who questions the rigid goal orientation associated with autonomous AI in the scenarios above. His most important point is that rigidly goal-oriented AI, which runs amok in the universe or saves humanity from every predicament, is not even conceivable. Outside its domain, the goal loses its meaning. The goal of a self-driving car to safely take the user to the destination has no meaning outside the domain of road traffic. Domain-specific AI can therefore not be generalized to the world as a whole, because the utility function loses its meaning outside the domain, long before the universe is turned into paper clips or the future of humanity is secured by an artificially good god.

This is, of course, an important philosophical point about goals and meaning, about specific domains and the world as a whole. The critique helps us to more realistically assess the risks and opportunities of future AI, without being bewitched by our images. At the same time, I get the impression that Totschnig continues to use AI as a projection screen for human self-images. He argues that future AI may well revise its ultimate goals as it develops a general understanding of the world. The weakness of the above scenarios was that they projected today’s domain-specific AI, not the general intelligence of humans. We then do not see the possibility of a genuinely human-like AI that self-critically reconsiders its final goals when new knowledge about the world makes it necessary. Truly human-equivalent AI would have full autonomy.

Projecting human self-images on future AI is not just a tendency, as far as I can judge, but a norm that governs the discussion. According to this norm, the wrong image is projected in the scenarios above. An image of today’s machines, not of our general human intelligence. Projecting the right self-image on future AI thus appears as an overall goal. Is the goal meaningful or should it be reconsidered self-critically?

These are difficult issues and my impression of the philosophical discussion may be wrong. If you want to judge for yourself, read the article: Fully autonomous AI.

Pär Segerdahl

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Pär Segerdahl, Associate Professor at the Centre for Research Ethics & Bioethics and editor of the Ethics Blog.

Totschnig, W. Fully Autonomous AI. Sci Eng Ethics 26, 2473–2485 (2020). https://doi.org/10.1007/s11948-020-00243-z

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Securing the future already from the beginning

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21 September, 2021 / / 1 Comment

Imagine if there was a reliable method for predicting and managing future risks, such as anything that could go wrong with new technology. Then we could responsibly steer clear of all future dangers, we could secure the future already now.

Of course, it is just a dream. If we had a “reliable method” for excluding future risks from the beginning, time would soon rush past that method, which then proved to be unreliable in a new era. Because we trusted the method, the method of managing future risks soon became a future risk in itself!

It is therefore impossible to secure the future from the beginning. Does this mean that we must give up all attempts to take responsibility for the future, because every method will fail to foresee something unpredictably new and therefore cause misfortune? Is it perhaps better not to try to take any responsibility at all, so as not to risk causing accidents through our imperfect safety measures? Strangely enough, it is just as impossible to be irresponsible for the future as it is to be responsible. You would need to make a meticulous effort so that you do not happen to cook a healthy breakfast or avoid a car collision. Soon you will wish you had a “safe method” that could foresee all the future dangers that you must avoid to avoid if you want to live completely irresponsibly. Your irresponsibility for the future would become an insurmountable responsibility.

Sorry if I push the notions of time and responsibility beyond their breaking point, but I actually think that many of us have a natural inclination to do so, because the future frightens us. A current example is the tendency to think that someone in charge should have foreseen the pandemic and implemented powerful countermeasures from the beginning, so that we never had a pandemic. I do not want to deny that there are cases where we can reason like that – “someone in charge should have…” – but now I want to emphasize the temptation to instinctively reason in such a way as soon as something undesirable occurs. As if the future could be secured already from the beginning and unwanted events would invariably be scandals.

Now we are in a new situation. Due to the pandemic, it has become irresponsible not to prepare (better than before) for risks of pandemics. This is what our responsibility for the future looks like. It changes over time. Our responsibility rests in the present moment, in our situation today. Our responsibility for the future has its home right here. It may sound irresponsible to speak in such a way. Should we sit back and wait for the unwanted to occur, only to then get the responsibility to avoid it in the future? The problem is that this objection once again pushes concepts beyond their breaking point. It plays around with the idea that the future can be foreseen and secured already now, a thought pattern that in itself can be a risk. A society where each public institution must secure the future within its area of ​​responsibility, risks kicking people out of the secured order: “Our administration demands that we ensure that…, therefore we need a certificate and a personal declaration from you, where you…” Many would end up outside the secured order, which hardly secures any order. And because the trouble-makers are defined by contrived criteria, which may be implemented in automated administration systems, these systems will not only risk making systematic mistakes in meeting real people. They will also invite cheating with the systems.

So how do we take responsibility for the future in a way that is responsible in practice? Let us first calm down. We have pointed out that it is impossible not to take responsibility! Just breathing means taking responsibility for the future, or cooking breakfast, or steering the car. Taking responsibility is so natural that no one needs to take responsibility for it. But how do we take responsibility for something as dynamic as research and innovation? They are already in the future, it seems, or at least at the forefront. How can we place the responsibility for a brave new world in the present moment, which seems to be in the past already from the beginning? Does not responsibility have to be just as future oriented, just as much at the forefront, since research and innovation are constantly moving towards the future, where they make the future different from the already past present moment?

Once again, the concepts are pushed beyond their breaking point. Anyone who reads this post carefully can, however, note a hopeful contradiction. I have pointed out that it is impossible to secure the future already now, from the beginning. Simultaneously, I point out that it is in the present moment that our responsibility for the future lies. It is only here that we take responsibility for the future, in practice. How can I be so illogical?

The answer is that the first remark is directed at our intellectual tendency to push the notions of time and responsibility beyond their limits, when we fear the future and wish that we could control it right now. The second remark reminds us of how calmly the concepts of time and responsibility work in practice, when we take responsibility for the future. The first remark thus draws a line for the intellect, which hysterically wants to control the future totally and already from the beginning. The second remark opens up the practice of taking responsibility in each moment.

When we take responsibility for the future, we learn from history as it appears in current memory, as I have already indicated. The experiences from the pandemic make it possible at present to take responsibility for the future in a different way than before. The not always positive experiences of artificial intelligence make it possible at present to take better responsibility for future robotics. The strange thing, then, is that taking responsibility presupposes that things go wrong sometimes and that we are interested in the failures. Otherwise we had nothing to learn from, to prepare responsibly for the future. It is really obvious. Responsibility is possible only in a world that is not fully secured from the beginning, a world where the undesirable happens. Life is contradictory. We can never purify security according to the one-sided demands of the intellect, for security presupposes the uncertain and the undesirable.

Against this philosophical background, I would like to recommend an article in the Journal of Responsible Innovation, which discusses responsible research and innovation in a major European research project, the Human Brain Project (HBP): From responsible research and innovation to responsibility by design. The article describes how one has tried to be foresighted and take responsibility for the dynamic research and innovation within the project. The article reflects not least on the question of how to continue to be responsible even when the project ends, within the European research infrastructure that is planned to be the project’s product: EBRAINS.

The authors are well aware that specific regulated approaches easily become a source of problems when they encounter the new and unforeseen. Responsibility for the future cannot be regulated. It cannot be reduced to contrived criteria and regulations. One of the most important conclusions is that responsibility from the beginning needs to be an integral part of research and innovation, rather than an external framework. Responsibility for the future requires flexibility, openness, anticipation, engagement and reflection. But what is all that?

Personally, I want to say that it is partly about accepting the basic ambiguity of life. If we never have the courage to soar in uncertainty, but always demand security and nothing but security, we will definitely undermine security. By being sincerely interested in the uncertain and the undesirable, responsibility can become an integral part of research and innovation.

Pär Segerdahl

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Pär Segerdahl, Associate Professor at the Centre for Research Ethics & Bioethics and editor of the Ethics Blog.

Bernd Carsten Stahl, Simisola Akintoye, Lise Bitsch, Berit Bringedal, Damian Eke, Michele Farisco, Karin Grasenick, Manuel Guerrero, William Knight, Tonii Leach, Sven Nyholm, George Ogoh, Achim Rosemann, Arleen Salles, Julia Trattnig & Inga Ulnicane. From responsible research and innovation to responsibility by design. Journal of Responsible Innovation. (2021) DOI: 10.1080/23299460.2021.1955613

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Ethically responsible robot development

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18 November, 2020 / / 1 Comment

Development of new technologies sometimes draws inspiration from nature. How do plants and animals solve the problem? An example is robotics, where one wants to develop better robots based on what neuroscience knows about the brain. How does the brain solve the problem?

Neuroscience, in turn, sees new opportunities to test hypotheses about the brain by simulating them in robots. Perhaps one can simulate how areas of the brain interact in patients with Parkinson’s disease, to understand how their tremor and other difficulties are caused.

Neuroscience-inspired robotics, so-called neurorobotics, is still at an early stage. This makes neurorobotics an excellent area for being ethically and socially more proactive than we have been in previous technological developments. That is, we can already begin to identify possible ethical and social problems surrounding technological development and counteract them before they arise. For example, we cannot close our eyes to gender and equality issues, but must continuously reflect on how our own social and cultural patterns are reflected in the technology we develop. We need to open our eyes to our own blind spots!

You can read more about this ethical shift in technology development in an article in Science and Engineering Ethics (with Manuel Guerrero from CRB as one of the authors). The shift is called Responsible Research and Innovation, and is exemplified in the article by ongoing work in the European research project, Human Brain Project.

Not only neuroscientists and technology experts are collaborating in this project to develop neurorobotics. Scholars from the humanities and social sciences are also involved in the work. The article itself is an example of this broad collaboration. However, the implementation of responsible research and development is also at an early stage. It still needs to find more concrete forms of work that make it possible not only to anticipate ethical and social problems and reflect on them, but also to act and intervene to influence scientific and technological development.

From being a framework built around research and development, ethics is increasingly integrated into research and development. Read the article if you want to think about this transition to a more reflective and responsible technological development.

Pär Segerdahl

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Pär Segerdahl, Associate Professor at the Centre for Research Ethics & Bioethics and editor of the Ethics Blog.

Aicardi, C., Akintoye, S., Fothergill, B.T. et al. Ethical and Social Aspects of Neurorobotics. Sci Eng Ethics 26, 2533–2546 (2020). https://doi.org/10.1007/s11948-020-00248-8

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What is required of an ethics of artificial intelligence?

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14 September, 2020 / / 1 Comment

I recently highlighted criticism of the ethics that often figures in the field of artificial intelligence (AI). An ethics that can handle the challenges that AI presents us with requires more than just beautifully formulated ethical principles, values ​​and guidelines. What exactly is required of an ethics of artificial intelligence?

Michele Farisco, Kathinka Evers and Arleen Salles address the issue in the journal Science and Engineering Ethics. For them, ethics is not primarily principles and guidelines. Ethics is rather an ongoing process of thinking: it is continual ethical reflection on AI. Their question is thus not what is required of an ethical framework built around AI. Their question is what is required of in-depth ethical reflection on AI.

The authors emphasize conceptual analysis as essential in all ethical reflection on AI. One of the big difficulties is that we do not know exactly what we are discussing! What is intelligence? What is the difference between artificial and natural intelligence? How should we understand the relationship between intelligence and consciousness? Between intelligence and emotions? Between intelligence and insightfulness?

Ethical problems about AI can be both practical and theoretical, the authors point out. They describe two practical and two theoretical problems to consider. One practical problem is the use of AI in activities that require emotional abilities that AI lacks. Empathy gives humans insight into other humans’ needs. Therefore, AI’s lack of emotional involvement should be given special attention when we consider using AI in, for example, child or elderly care. The second practical problem is the use of AI in activities that require foresight. Intelligence is not just about reacting to input from the environment. A more active, foresighted approach is often needed, going beyond actual experience and seeing less obvious, counterintuitive possibilities. Crying can express pain, joy and much more, but AI cannot easily foresee less obvious possibilities.

Two theoretical problems are also mentioned in the article. The first is whether AI in the future may have morally relevant characteristics such as autonomy, interests and preferences. The second problem is whether AI can affect human self-understanding and create uncertainty and anxiety about human identity. These theoretical problems undoubtedly require careful analysis – do we even know what we are asking? In philosophy we often need to clarify our questions as we go along.

The article emphasizes one demand in particular on ethical analysis of AI. It should carefully consider morally relevant abilities that AI lacks, abilities needed to satisfy important human needs. Can we let a cute kindergarten robot “comfort” children when they scream with joy or when they injure themselves so badly that they need nursing?

Pär Segerdahl

Written by…

Pär Segerdahl, Associate Professor at the Centre for Research Ethics & Bioethics and editor of the Ethics Blog.

Farisco, M., Evers, K. & Salles, A. Towards establishing criteria for the ethical analysis of Artificial Intelligence. Science and Engineering Ethics (2020). https://doi.org/10.1007/s11948-020-00238-w

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Ethics as renewed clarity about new situations

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26 August, 2020 / / 1 Comment

An article in the journal Big Data & Society criticizes the form of ethics that has come to dominate research and innovation in artificial intelligence (AI). The authors question the same “framework interpretation” of ethics that you could read about on the Ethics Blog last week. However, with one disquieting difference. Rather than functioning as a fence that can set the necessary boundaries for development, the framework risks being used as ethics washing by AI companies that want to avoid legal regulation. By referring to ethical self-regulation – beautiful declarations of principles, values ​​and guidelines – one hopes to be able to avoid legal regulation, which could set important limits for AI.

The problem with AI ethics as “soft ethics legislation” is not just that it can be used to avoid necessary legal regulation of the area. The problem is above all, according to the SIENNA researchers who wrote the article, that a “law conception of ethics” does not help us to think clearly about new situations. What we need, they argue, is an ethics that constantly renews our ability to see the new. This is because AI is constantly confronting us with new situations: new uses of robots, new opportunities for governments and companies to monitor people, new forms of dependence on technology, new risks of discrimination, and many other challenges that we may not easily anticipate.

The authors emphasize that such eye-opening AI ethics requires close collaboration with the social sciences. That, of course, is true. Personally, I want to emphasize that an ethics that renews our ability to see the new must also be philosophical in the deepest sense of the word. To see the new and unexpected, you cannot rest comfortably in your professional competence, with its established methods, theories and concepts. You have to question your own disciplinary framework. You have to think for yourself.

Read the article, which has already attracted well-deserved attention.

Pär Segerdahl

Written by…

Pär Segerdahl, Associate Professor at the Centre for Research Ethics & Bioethics and editor of the Ethics Blog.

Anaïs Rességuier, Rowena Rodrigues. 2020. AI ethics should not remain toothless! A call to bring back the teeth of ethics. Big Data & Society

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What is a moral machine?

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1 April, 2020 / / 3 Comments

I recently read an article about so-called moral robots, which I found clarifying in many ways. The philosopher John-Stewart Gordon points out pitfalls that non-ethicists – robotics researchers and AI programmers – may fall into when they try to construct moral machines. Simply because they lack ethical expertise.

The first pitfall is the rookie mistakes. One might naively identify ethics with certain famous bioethical principles, as if ethics could not be anything but so-called “principlism.” Or, it is believed that computer systems, through automated analysis of individual cases, can “learn” ethical principles and “become moral,” as if morality could be discovered experientially or empirically.

The second challenge has to do with the fact that the ethics experts themselves disagree about the “right” moral theory. There are several competing ethical theories (utilitarianism, deontology, virtue ethics and more). What moral template should programmers use when getting computers to solve moral problems and dilemmas that arise in different activities? (Consider self-driving cars in difficult traffic situations.)

The first pitfall can be addressed with more knowledge of ethics. How do we handle the second challenge? Should we allow programmers to choose moral theory as it suits them? Should we allow both utilitarian and deontological robot cars on our streets?

John-Stewart Gordon’s suggestion is that so-called machine ethics should focus on the similarities between different moral theories regarding what one should not do. Robots should be provided with a binding list of things that must be avoided as immoral. With this restriction, the robots then have leeway to use and balance the plurality of moral theories to solve moral problems in a variety of ways.

In conclusion, researchers and engineers in robotics and AI should consult the ethics experts so that they can avoid the rookie mistakes and understand the methodological problems that arise when not even the experts in the field can agree about the right moral theory.

All this seems both wise and clarifying in many ways. At the same time, I feel genuinely confused about the very idea of ​​”moral machines” (although the article is not intended to discuss the idea, but focuses on ethical challenges for engineers). What does the idea mean? Not that I doubt that we can design artificial intelligence according to ethical requirements. We may not want robot cars to avoid collisions in city traffic by turning onto sidewalks where many people walk. In that sense, there may be ethical software, much like there are ethical funds. We could talk about moral and immoral robot cars as straightforwardly as we talk about ethical and unethical funds.

Still, as I mentioned, I feel uncertain. Why? I started by writing about “so-called” moral robots. I did so because I am not comfortable talking about moral machines, although I am open to suggestions about what it could mean. I think that what confuses me is that moral machines are largely mentioned without qualifying expressions, as if everyone ought to know what it should mean. Ethical experts disagree on the “right” moral theory. However, they seem to agree that moral theory determines what a moral decision is; much like grammar determines what a grammatical sentence is. With that faith in moral theory, one need not contemplate what a moral machine might be. It is simply a machine that makes decisions according to accepted moral theory. However, do machines make decisions in the same sense as humans do?

Maybe it is about emphasis. We talk about ethical funds without feeling dizzy because a stock fund is said to be ethical (“Can they be humorous too?”). There is no mythological emphasis in the talk of ethical funds. In the same way, we can talk about ethical robot cars without feeling dizzy as if we faced something supernatural. However, in the philosophical discussion of machine ethics, moral machines are sometimes mentioned in a mythological way, it seems to me. As if a centaur, a machine-human, will soon see the light of day. At the same time, we are not supposed to feel dizzy concerning these brave new centaurs, since the experts can spell out exactly what they are talking about. Having all the accepted templates in their hands, they do not need any qualifying expressions!

I suspect that also ethical expertise can be a philosophical pitfall when we intellectually approach so-called moral machines. The expert attitude can silence the confusing questions that we all need time to contemplate when honest doubts rebel against the claim to know.

Pär Segerdahl

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Pär Segerdahl, Associate Professor at the Centre for Research Ethics & Bioethics and editor of the Ethics Blog.

Gordon, J. Building Moral Robots: Ethical Pitfalls and Challenges. Sci Eng Ethics 26, 141–157 (2020).

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