The Ethics Blog

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

Month: April 2024

Objects that behave humanly

smiling robot making eye contact
23 April, 2024 / / 1 Comment

Many forms of artificial intelligence could be considered objects that behave humanly. However, it does not take much for us humans to personify non-living objects. We get angry at the car that does not start or the weather that does not let us have a picnic, as if they were against us. Children spontaneously personify simple toys and can describe the relationship between geometric shapes as, “the small circle is trying to escape from the big triangle.”

We are increasingly encountering artificial intelligence designed to give a human impression, for example in the form of chatbots for customer service when shopping online. Such AI can even be equipped with personal traits, a persona that becomes an important part of the customer experience. The chatbot can suggest even more products for you and effectively generate additional sales based on the data collected about you. No wonder the interest in developing human-like AI is huge. Part of it has to do with user-friendliness, of course, but at the same time, an AI that you find personally attractive will grab your attention. You might even like the chatbot or feel it would be impolite to turn it off. During the time that the chatbot has your attention, you are exposed to increasingly customized advertising and receive more and more package offers.

You can read about this and much more in an article about human relationships with AI designed to give a human impression: Human/AI relationships: challenges, downsides, and impacts on human/human relationships. The authors discuss a large number of examples of such AI, ranging from the chatbots above to care robots and AI that offers psychotherapy, or AI that people chat with to combat loneliness. The opportunities are great, but so are the challenges and possible drawbacks, which the article highlights.

Perhaps particularly interesting is the insight into how effectively AI can create confusion by exposing us to objects equipped with human response patterns. Our natural tendency to anthropomorphize non-human things meets high-tech efforts to produce objects that are engineered to behave humanly. Here it is no longer about imaginatively projecting social relations onto non-human objects, as in the geometric example above. In interaction with AI objects, we react to subtle social cues that the objects are equipped with. We may even feel a moral responsibility for such AI and grieve when companies terminate or modify it.

The authors urge caution so that we do not overinterpret AI objects as persons. At the same time, they warn of the risk that, by avoiding empathic responses, we become less sensitive to real people in need. Truly confusing!

Pär Segerdahl

Written by…

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

Zimmerman, A., Janhonen, J. & Beer, E. Human/AI relationships: challenges, downsides, and impacts on human/human relationships. AI Ethics (2023). https://doi.org/10.1007/s43681-023-00348-8

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A way out of the Babylonian confusion of tongues in the theorizing of consciousness?

Dictionary "Collaborate", Image by Dianne Hope from Pixabay
16 April, 2024 / / 1 Comment

There is today a wide range of competing theories, each in its own way trying to account for consciousness in neurobiological terms. Parallel to the “Babylonian confusion of tongues” and inability to collaborate that this entails in the theorizing of consciousness, progress has been made in the empirical study of the brain. Advanced methods for imaging and measuring the brain and its activities map structures and functions that are possibly relevant for consciousness. The problem is that these empirical data once again inspire a wide range of theories about the place of consciousness in the brain.

It has been pointed out that a fragmented intellectual state such as this, where competing schools of thought advocate their own theories based on their own starting points – with no common framework or paradigm within which the proposals can be compared and assessed – is typical of a pre-scientific stage of a possibly nascent science. Given that the divergent theories each claim scientific status, this is of course troubling. But maybe the theories are not as divergent as they seem?

It has been suggested that several of the theories, upon closer analysis, possibly share certain fundamental ideas about consciousness, which could form the basis of a future unified theory. Today I want to recommend an article that self-critically examines this hope for a way out of the Babylonian confusion. If the pursuit of a unified theory of consciousness is not to degenerate into a kind of “manufactured uniformity,” we must first establish that the theories being integrated are indeed comparable in relevant respects. But can we identify such common denominators among the competing theories, which could support the development of an overarching framework for scientific research? That is the question that Kathinka Evers, Michele Farisco and Cyriel Pennartz investigate for some of the most debated neuroscientifically oriented theories of consciousness.

What do the authors conclude? Something surprising! They come to the conclusion that it is actually quite possible to identify a number of common denominators, which show patterns of similarities and differences among the theories, but that this is still not the way to an overall theory of consciousness that supports hypotheses that can be tested experimentally. Why? Partly because the common denominators, such as “information,” are sometimes too general to function as core concepts in research specifically about consciousness. Partly because theories that have common denominators can, after all, be conceptually very different.

The authors therefore suggest, as I understand them, that a more practicable approach could be to develop a common methodological approach to testing hypotheses about relationships between consciousness and the brain. It is perhaps only in the empirical workshop, open to the unexpected, so to speak, that a scientific framework, or paradigm, can possibly begin to take shape. Not by deliberately formulating unified theory based on the identification of common denominators among competing theories, which risks manufacturing a facade of uniformity.

The article is written in a philosophically open-minded spirit, without ties to specific theories. It can thereby stimulate the creative collaboration that has so far been inhibited by self-absorbed competition between schools of thought. Read the article here: Assessing the commensurability of theories of consciousness: On the usefulness of common denominators in differentiating, integrating and testing hypotheses.

I would like to conclude by mentioning an easily neglected aspect of how scientific paradigms work (according to Thomas Kuhn). A paradigm does not only generate possible explanations of phenomena. It also generates the problems that researchers try to solve within the paradigm. Quantum mechanics and evolutionary biology enabled new questions that made nature problematic in new explorable ways. A possible future paradigm for scientific consciousness research would, if this is correct, not answer the questions about consciousness that baffle us today (at least not without first reinterpreting them). Rather, it would create new, as yet unasked questions, which are explorable within the paradigm that generates them.

The authors of the article may therefore be right that the most fruitful thing at the moment is to ask probing questions that help us delineate what actually lends itself to investigation, rather than to start by manufacturing overall theoretical uniformity. The latter approach would possibly put the cart before the horse.

Pär Segerdahl

Written by…

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

K. Evers, M. Farisco, C.M.A. Pennartz, “Assessing the commensurability of theories of consciousness: On the usefulness of common denominators in differentiating, integrating and testing hypotheses,” Consciousness and Cognition, Volume 119, 2024,

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A strategy for a balanced discussion of conscious AI

Image by Gerd Altman on Pixabay
9 April, 2024 / / 2 Comments

Science and technology advance so rapidly that it is hard to keep up with them. This is true not only for the general public, but also for the scientists themselves and for scholars from fields like ethics and regulation, who find it increasingly difficult to predict what will come next. Today AI is among the most advanced scientific endeavors, raising both significant expectations and more or less exaggerated worries. This is mainly due to the fact that AI is a concept so emotionally, socially, and politically charged as to make a balanced evaluation very difficult. It is even more so when capacities and features that are considered almost uniquely human, or at least shared with a limited number of other animals, are attributed to AI. This is the case with consciousness.

Recently, there has been a lively debate about the possibility of developing conscious AI. What are the reasons for this great interest? I think it has to do with the mentioned rapid advances in science and technology, as well as new intersections between different disciplines. Specifically, I think that three factors play an important role: the significant advancement in understanding the cerebral bases of conscious perception, the impressive achievements of AI technologies, and the increasing interaction between neuroscience and AI. The latter factor, in particular, resulted in so-called brain-inspired AI, a form of AI that is explicitly modeled on our brains.

This growing interest in conscious AI cannot ignore certain risks of varying relevance, including theoretical, practical, and ethical relevance. Theoretically, there is not a shared, overarching theory or definition of consciousness. Discussions about what consciousness is, what the criteria for a good scientific theory should be, and how to compare the various proposed theories of consciousness are still open and difficult to resolve.

Practically, the challenge is how to identify conscious systems. In other words, what are the indicators that reliably indicate whether a system, either biological or artificial, is conscious?

Finally, at the ethical level several issues arise. Here the discussion is very lively, with some calling for an international moratorium on all attempts to build artificial consciousness. This extreme position is motivated by the need for avoiding any form of suffering, including possibly undetectable artificial forms of suffering. Others question the very reason for working towards conscious AI: why should we open another, likely riskier box, when society cannot really handle the impact of AI, as illustrated by Large Language Models? For instance, chatbots like ChatGPT show an impressive capacity to interact with humans through natural language, which creates a strong feeling that these AI systems have features like consciousness, intentionality, and agency, among others. This attribution of human qualities to AI eventually impacts the way we think about it, including how much weight and value we give to the answers that these chatbots provide.

The two arguments above illustrate possible ethical concerns that can be raised against the development of conscious artificial systems. Yet are the concerns justified? In a recent chapter, I propose a change in the underlying approach to the issue of artificial consciousness. This is to avoid the risk of vague and not sufficiently multidimensional analyses. My point is that consciousness is not a unified, abstract entity, but rather like a prism, which includes different dimensions that could possibly have different levels. Based on a multidimensional view of consciousness, in a previous paper I contributed a list of indicators that are relevant also for identifying consciousness in artificial systems. In principle, it is possible that AI can manifest some dimensions of consciousness (for instance, those related to sophisticated cognitive tasks) while lacking others (for instance, those related to emotional or social tasks). In this way, the indicators provide not only a practical tool for identifying conscious systems, but also an ethical tool to make the discussion on possible conscious AI more balanced and realistic. The question whether some AI is conscious or not cannot be considered a yes/no question: there are several nuances that make the answer more complex.

Indeed, the indicators mentioned above are affected by a number of limitations, including the fact that they are developed for humans and animals, not specifically for AI. For this reason, research is still ongoing on how to adapt these indicators or possibly develop new indicators specific for AI. If you want to read more, you can find my chapter here: The ethical implications of indicators of consciousness in artificial systems.

Written by…

Michele Farisco, Postdoc Researcher at Centre for Research Ethics & Bioethics, working in the EU Flagship Human Brain Project.

Michele Farisco. The ethical implications of indicators of consciousness in artificial systems. Developments in Neuroethics and Bioethics. Available online 1 March 2024. https://doi.org/10.1016/bs.dnb.2024.02.009

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