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

Tag: philosophy (Page 1 of 16)

Self-confidence in the midst of uncertainty

Feeling confident is natural when we have the knowledge that the task requires. However, self-confidence can be harmful if we think that we know what we do not know. It can be really problematic if we make a habit of pretending that we know. Perhaps because we demand it of ourselves.

There is also another kind of self-confidence, which can seem unnatural. I am thinking of a rarely noticed form of self-confidence, which can awaken just when we are uncertain about how to think and act. But how can self-confidence arise precisely when we are uncertain? It sounds not only unnatural, but also illogical. And was it not harmful to exhibit self-confidence in such situations?

I am thinking of the self-confidence to be just as uncertain as we are, because our uncertainty is a fact that we are certain of: I do not know. It is easy to overlook the fact that even uncertainty is a reality that can be ascertained and investigated in ourselves. Sometimes it is important to take note of our uncertainty. That is sticking to the facts too!

What happens if we do not trust uncertainty when we are uncertain? I think we then tend to seek guidance from others, who seem to know what we do not know. It seems not only natural, but also logical. It is reasonable to do so, of course, if relevant knowledge really exists elsewhere. Asking others, who can be judged to know better, also requires a significant measure of self-confidence and good judgment, in the midst of uncertainty.

But suppose we instinctively seek guidance from others as soon as we are uncertain, because we do not dare to stick to uncertainty in such moments. What happens if we always run away from uncertainty, without stopping and paying attention to it, as if uncertainty were something impermissible? In such a judgmental attitude to uncertainty, knowledge and certainty can become a demand that we feel must be met, towards ourselves and towards each other, if only as a facade. We are then back where we started, in pretended knowledge, which now might become a collective high-risk game and not just an individual bad habit.

Collective knowledge games can of course work, if sufficiently many influential players have the knowledge that the tasks require and knowledge is disseminated in a well-organized manner. Maybe we think that it should be possible to build such a society, a secure knowledge society. The question I wonder about is how sustainable this is in the long run, if the emphasis on certainty does not simultaneously emphasize also uncertainty and questioning. Not for the sake of questioning, but because uncertainty is also a fact that needs attention.

In philosophy and ethics, it is often uncertainty that primarily drives the work. This may sound strange, but even uncertainty can be investigated. If we ask a tentative question about something we sincerely wonder about, clearer questions can soon arise that we continue to wonder about, and soon the investigation will begin. The investigation comes to life because we dare to trust ourselves, because we dare to give ourselves time to think, in the midst of uncertainty, which can become clarity if we do not run away from it. In the investigation, we can of course notice that we need more knowledge about specific issues, knowledge that is acquired from others or that we ourselves develop through empirical studies. But it is not only specific knowledge that informs the investigation. The work with the questions that express our uncertainty clarifies ourselves and makes our thinking clearer. Knowledge gets a well-considered context, where it is needed, which enlightens knowledge.

A “pure” game of knowledge is hardly sustainable in the long run, if its demands are not open also to the other side of knowledge, to the uncertainty that can be difficult to separate from ourselves. Such openness requires that we trust not only the rules of the game, but also ourselves. But do we dare to trust ourselves when we are uncertain?

I think we dare, if we see uncertainty as a fact that can be investigated and clarified, instead of judging it as something dangerous that should not be allowed to be a fact. That is when it can become dangerous.

Pär Segerdahl

Written by…

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

This post in Swedish

Thinking about thinking

How can we detect consciousness in brain-damaged patients?

Detecting consciousness in brain-damaged patients can be a huge challenge and the results are often uncertain or misinterpreted. In a previous post on this blog I described six indicators of consciousness that I introduced together with a neuroscientist and another philosopher. Those indicators were originally elaborated targeting animals and AI systems. Our question was: what capacities (deducible from behavior and performance or relevant cerebral underpinnings) make it reasonable to attribute consciousness to these non-human agents? In the same post, I mentioned that we were engaged in a multidisciplinary exploration of the clinical relevance of selected indicators, specifically for testing them on patients with Disorders of Consciousness (DoCs, for instance, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State, Cognitive-Motor Dissociation). While this multidisciplinary work is still in progress, we recently published an ethical reflection on the clinical relevance of the indicators of consciousness, taking DoCs as a case study.

To recapitulate, indicators of consciousness are conceived as particular capacities that can be deduced from the behavior or cognitive performance of a subject and that serve as a basis for a reasonable inference about the level of consciousness of the subject in question. Importantly, also the neural correlates of the relevant behavior or cognitive performance may make possible deducing the indicators of consciousness.  This implies the relevance of the indicators to patients with DoCs, who are often unable to behave or to communicate overtly. Responses in the brain can be used to deduce the indicators of consciousness in these patients.

On the basis of this relevance, we illustrate how the different indicators of consciousness might be applied to patients with DoCs with the final goal of contributing to improve the assessment of their residual conscious activity. In fact, a still astonishing rate of misdiagnosis affects this clinical population. It is estimated that up to 40 % of patients with DoCs are wrongly diagnosed as being in Vegetative State/Unresponsive Wakefulness Syndrome, while they are actually in a Minimally Conscious State. The difference of these diagnoses is not minimal, since they have importantly different prognostic implications, which raises a huge ethical problem.

We also argue for the need to recognize and explore the specific quality of the consciousness possibly retained by patients with DoCs. Because of the devastating damages of their brain, it is likely that their residual consciousness is very different from that of healthy subjects, usually assumed as a reference standard in diagnostic classification. To illustrate, while consciousness in healthy subjects is characterized by several distinct sensory modalities (for example, seeing, hearing and smelling), it is possible that in patients with DoCs, conscious contents (if any) are very limited in sensory modalities. These limitations may be evaluated based on the extent of the brain damage and on the patients’ residual behaviors (for instance, sniffing for smelling). Also, consciousness in healthy subjects is characterized by both dynamics and stability: it includes both dynamic changes and short-term stabilization of contents. Again, in the case of patients with DoCs, it is likely that their residual consciousness is very unstable and flickering, without any capacity for stabilization. If we approach patients with DoCs without acknowledging that consciousness is like a spectrum that accommodates different possible shapes and grades, we exclude a priori the possibility of recognizing the peculiarity of consciousness possibly retained by these patients.

The indicators of consciousness we introduced offer a potential help to identify the specific conscious abilities of these patients. While in this paper we argue for the rationale behind the clinical use of these indicators, and for their relevance to patients with DoCs, we also acknowledge that they open up new lines of research with concrete application to patients with DoCs. As already mentioned, this more applied work is in progress and we are confident of being able to present relevant results in the weeks to come.

Written by…

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

Farisco, M., Pennartz, C., Annen, J. et al. Indicators and criteria of consciousness: ethical implications for the care of behaviourally unresponsive patients. BMC Med Ethics 2330 (2022). https://doi.org/10.1186/s12910-022-00770-3

We have a clinical perspective

Fact resistance, human nature and contemplation

Sometimes we all resist facts. I saw a cyclist slip on the icy road. When I asked if it went well, she was on her feet in an instant and denied everything: “I did not fall!” It is human to deny facts. They can hurt and be disturbing.

What are we resisting? The usual answer is that fact-resistant individuals or groups resist facts about the world around us, such as statistics on violent crime, on vaccine side effects, on climate change or on the spread of disease. It then becomes natural to offer resistance to fact resistance by demanding more rigour in the field of knowledge. People should learn to turn more rigorously to the world they live in! The problem is that fact-resistant attitudes do just that. They are almost bewitched by the world and by the causes of what are perceived as outrageous problems in it. And now we too are bewitched by fact resistance and speculate about the causes of this outrageous problem.

Of course, we believe that our opposition is justified. But who does not think so? Legitimate resistance is met by legitimate resistance, and soon the conflict escalates around its double spiral of legitimacy. The possibility of resolving it is blocked by the conflict itself, because all parties are equally legitimate opponents of each other. Everyone hears their own inner voices warning them from acknowledging their mistakes, from acknowledging their uncertainty, from acknowledging their human resistance to reality, as when we fall off the bike and wish it had never happened. The opposing side would immediately seize the opportunity! Soon, our mistake is a scandal on social media. So we do as the person who slipped on the icy road, we deny everything without thinking: “I was not wrong, I had my own facts!” We ignore the fact that life thereby becomes a lie, because our inner voices warn us from acknowledging our uncertainty. We have the right to be recognized, our voices insist, at least as an alternative to the “established view.”

Conflicts give us no time for reflection. Yet, there is really nothing stopping us from sitting down, in the midst of conflict, and resolving it within ourselves. When we give ourselves time to think for ourselves, we are freer to acknowledge our uncertainty and examine our spirals of thought. Of course, this philosophical self-examination does not resolve the conflict between legitimate opponents which escalates around us as increasingly impenetrable and real. It only resolves the conflict within ourselves. But perhaps our thoughtful philosophical voice still gives a hint of how, just by allowing us to soar in uncertainty, we already see the emptiness of the conflict and are free from it?

If we more often dared to soar in uncertainty, if it became more permissible to say “I do not know,” if we listened more attentively to thoughtful voices instead of silencing them with loud knowledge claims, then perhaps fact resistance also decreases. Perhaps fact resistance is not least resistance to an inner fact. To a single inner fact. What fact? Our insecurity as human beings, which we do not permit ourselves. But if you allow yourself to slip on the icy road, then you do not have to deny that you did!

A more thoughtful way of being human should be possible. We shape the societies that shape us.

Pär Segerdahl

Written by…

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

This post in Swedish

We care about communication

How can neuroethics and AI ethics join their forces?

As I already wrote on this blog, there has been an explosion of AI in recent years. AI affects so many aspects of our lives that it is virtually impossible to avoid interacting with it. Since AI has such an impact, it must be examined from an ethical point of view, for the very basic reason that it can be developed and/or used for both good and evil.

In fact, AI ethics is becoming increasingly popular nowadays. As it is a fairly young discipline, even though it has roots in, for example, digital and computer ethics, the question is open about its status and methodology. To simplify the debate, the main trend is to conceive AI ethics in terms of practical ethics, for example, with a focus on the impact of AI on traditional practices in education, work, healthcare, entertainment, among others. In addition to this practically oriented analysis, there is also attention to the impact of AI on the way we understand our society and ourselves as part of it.

In this debate about the identity of AI ethics, the need for a closer collaboration with neuroethics has been briefly pointed out, but so far no systematic reflection has been made on this need. In a new article, I propose, together with Kathinka Evers and Arleen Salles, an argument to justify the need for closer collaboration between neuroethics and AI ethics. In a nutshell, even though they both have specific identities and their topics do not completely overlap, we argue that neuroethics can complement AI ethics for both content-related and methodological reasons.

Some of the issues raised by AI are related to fundamental questions that neuroethics has explored since its inception. Think, for example, of topics such as intelligence: what does it mean to be intelligent? In what sense can a machine be qualified as an intelligent agent? Could this be a misleading use of words? And what ethical implications can this linguistic habit have, for example, on how we attribute responsibility to machines and to humans? Another issue that is increasingly gaining ground in AI ethics literature, as I wrote on this blog, is the conceivability and the possibility of artificial consciousness. Neuroethics has worked extensively on both intelligence and consciousness, combining applied and fundamental analyses, which can serve as a source of relevant information for AI ethics.

In addition to the above content-related reasons, neuroethics can also provide AI ethics with a methodological model. To illustrate, the kind of conceptual clarification performed in fundamental neuroethics can enrich the identification and assessment of the practical ethical issues raised by AI. More specifically, neuroethics can provide a three-step model of analysis to AI ethics: 1. Conceptual relevance: can specific notions, such as autonomy, be attributed to AI? 2. Ethical relevance: are these specific notions ethically salient (i.e., do they require ethical evaluation)? 3. Ethical value: what is the ethical significance and the related normative implications of these specific notions?

This three-step approach is a promising methodology for ethical reflection about AI which avoids the trap anthropocentric self-projection, a risk that actually affects both the philosophical reflection on AI and its technical development.

In this way, neuroethics can contribute to avoiding both hypes and disproportionate worries about AI, which are among the biggest challenges facing AI ethics today.

Written by…

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

Farisco, M., Evers, K. & Salles, A. On the Contribution of Neuroethics to the Ethics and Regulation of Artificial Intelligence. Neuroethics 15, 4 (2022). https://doi.org/10.1007/s12152-022-09484-0

We transcend disciplinary borders

Images of good and evil artificial intelligence

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

Written by…

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

This post in Swedish

We like critical thinking

Digital twins, virtual brains and the dangers of language

A new computer simulation technology has begun to be introduced, for example, in the manufacturing industry. The computer simulation is called a digital twin, which challenges me to bring to life for the reader what something that sounds so imaginative can be in reality.

The most realistic explanation I can find actually comes from Harry Potter’s world. Do you remember the map of Hogwarts, which not only shows all the rooms and corridors, but also the steps in real time of those who sneak around the school? A similar map can be easily created in a computer environment by connecting the map in the computer to sensors in the floor of the building that the map depicts. Immediately you have an interactive digital map of the building that is automatically updated and shows people’s movements in it. Imagine further that the computer simulation can make calculations that predict crowds that exceed the authorities’ recommendations, and that it automatically sends out warning messages via a speaker system. As far as I understand, such an interactive digital map can be called a digital twin for an intelligent house.

Of course, this is a revolutionary technology. The architect’s drawing in a computer program gets extended life in both the production and maintenance of the building. The digital simulation is connected to sensors that update the simulation with current data on relevant factors in the construction process and thereafter in the finished building. The building gets a digital twin that during the entire life cycle of the building automatically contacts maintenance technicians when the sensors show that the washing machines are starting to wear out or that the air is not circulating properly.

The scope of use for digital twins is huge. The point of them, as I understand it, is not that they are “exact virtual copies of reality,” whatever that might mean. The point is that the computer simulation is linked to the simulated object in a practically relevant way. Sensors automatically update the simulation with relevant data, while the simulation automatically updates the simulated object in relevant ways. At the same time, users, manufacturers, maintenance technicians and other actors are updated, who easily can monitor the object’s current status, opportunities and risks, wherever they are in the world.

The European flagship project Human Brain Project plans to develop digital twins of human brains by building virtual brains in a computer environment. In a new article, the philosophers Kathinka Evers and Arleen Salles, who are both working in the project, examine the enormous challenges involved in developing digital twins of living human brains. Is it even conceivable?

The authors compare types of objects that can have digital twins. It can be artefacts such as buildings and cars, or natural inanimate phenomena such as the bedrock at a mine. But it could also be living things such as the heart or the brain. The comparisons in the article show that the brain stands out in several ways, all of which make it unclear whether it is reasonable to talk about digital twins of human brains. Would it be more appropriate to talk about digital cousins?

The brain is astronomically complex and despite new knowledge about it, it is highly opaque to our search for knowledge. How can we talk about a digital twin of something that is as complex as a galaxy and as unknown as a black hole? In addition, the brain is fundamentally dynamically interactive. It is connected not only with the body but also with culture, society and the world around it, with which it develops in uninterrupted interaction. The brain almost merges with its environment. Does that imply that a digital twin would have to be a twin of the brain-body-culture-society-world, that is, a digital twin of everything?

No, of course not. The aim of the project is to find specific medical applications of the new computer simulation technology. By developing digital twins of certain aspects of certain parts of patients’ brains, it is hoped that one can improve and individualize, for example, surgical procedures for diseases such as epilepsy. Just as the map from Harry Potter’s world shows people’s steps in real time, the digital twin of the brain could follow the spread of certain nerve impulses in certain parts of the patient’s brain. This can open up new opportunities to monitor, diagnose, predict and treat diseases such as epilepsy.

Should we avoid the term digital twin when talking about the brain? Yes, it would probably be wiser to talk about digital siblings or digital cousins, argue Kathinka Evers and Arleen Salles. Although experts in the field understand its technical use, the term “digital twin” is linguistically risky when we talk about human brains. It easily leads the mind astray. We imagine that the digital twin must be an exact copy of a human’s whole brain. This risks creating unrealistic expectations and unfounded fears about the development. History shows that language also contains other dangers. Words come with normative expectations that can have ethical and social consequences that may not have been intended. Talking about a digital twin of a mining drill is probably no major linguistic danger. But when it comes to the brains of individual people, the talk of digital twins can become a new linguistic arena where we reinforce prejudices and spread fears.

After reading some popular scientific explanations of digital twins, I would like to add that caution may be needed also in connection with industrial applications. After all, the digital twin of a mining drill is not an “exact virtual copy of the real drill” in some absolute sense, right down to the movements of individual atoms. The digital twin is a copy in the practical sense that the application makes relevant. Sometimes it is enough to copy where people put their feet down, as in Harry Potter’s world, whose magic unexpectedly helps us understand the concept of a digital twin more realistically than many verbal explanations do. Explaining words with the help of other words is not always clarifying, if all the words steer thought in the same direction. The words “copy” and “replica” lead our thinking just as right and just as wrong as the word “twin” does.

If you want to better understand the challenges of creating digital twins of human brains and the importance of conceptual clarity concerning the development, read the philosophically elucidatory article: Epistemic Challenges of Digital Twins & Virtual Brains: Perspectives from Fundamental Neuroethics.

Pär Segerdahl

Written by…

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

Evers, Kathinka & Salles, Arleen. (2021). Epistemic Challenges of Digital Twins & Virtual Brains: Perspectives from Fundamental Neuroethics. SCIO: Revista de Filosofía. 27-53. 10.46583 / scio_2021.21.846

This post in Swedish

Minding our language


What does it mean to be inspired by someone? Think of these inspired music albums where artists lovingly pay tribute to a great musician by making their own interpretations of the songs. These interpretations often express deep gratitude for the inspiration received from the musician. We can feel similar gratitude to inspiring people in many different areas.

Why are we inspired by inspiring people? Here is a tempting picture. The person who inspires us has something that we lack. To be inspired is to want what the inspiring person has: “I also want to be able to…”; “I want to be as good as…” and so on. That is why we imitate those who inspire us. That is why we train hard. By imitating, by practicing, the inspiring person’s abilities can be transferred to us who lack them.

This could be called a pneumatic picture of inspiration. The inspiring one is, so to speak, an air tank with overpressure. The rest of us are tanks with negative pressure. The pressure difference causes the inspiration. By imitating the inspiring person, the pressure difference is evened out. The pressure migrates from the inspiring to the inspired. We inhale the air that flows from the tank with overpressure.

This picture is certainly partly correct, but it is hardly the whole truth about inspiration. I am not a musician. There is a big difference in pressure between me and any musician. Why does this pressure difference not cause inspiration? Why do I not start imitating musicians, training hard so that some of the musicians’ overpressure is transferred to me?

The pneumatic picture is not the whole truth, other pictures of inspiration are possible. Here is one. Maybe inspiration is not aroused by difference, not by the fact that we lack what the inspiring person has. Perhaps inspiration is aroused by similarity, by the fact that we sense a deep affinity with the one who inspires us. When we are inspired, we recognize ourselves in the one who inspires us. We discover something we did not know about ourselves. Seeds that we did not know existed in us begin to sprout, when the inspiring person makes us aware that we have the same feeling, the same passion, the same creativity… At that moment, the inspiration is aroused in us.

In this alternative picture of inspiration, there is no transfer of abilities from the inspiring one to the inspired ones. Rather, the abilities grow spontaneously in the inspired ones themselves, when they sense their affinity with the inspiring one. In the inspiring person, this growth has already taken place. Creativity has had time to develop and take shape, so that the rest of us can recognize ourselves in it. This alternative image of inspiration also provides an alternative image of human history in different areas. We are familiar with historical representations of how predecessors inspired their successors, as if the abilities of the predecessors were transferred horizontally in time. In the alternative picture, history is not just horizontal. Above all, it has a vertical depth dimension in each of us. Growing takes place vertically in each new generation, much like seeds sprout in the earth and grow towards the sky. History is, in this alternative image, a series of vertical growing, where it is difficult to distinguish the living creativity in the depth dimension from the imitation on the surface.

Why am I writing a post about inspiration? Apart from the fact that it is inspiring to think about something as vital as inspiration, I want to show how unnoticed we make pictures of facts. We do not see that it is actually just pictures, which could be replaced by completely different pictures. I learned this from the philosopher Ludwig Wittgenstein, who inspired me to examine philosophical questions myself: questions which surprisingly often arise because we are captured in our images of things. Our captivity in certain images prevents us from seeing other possibilities and obvious facts.

In addition, I want to show that it really makes a difference if we are caught in our pictures of things or open to the possibility of completely different pictures. It has been a long time since I wrote about ape language research on this blog, but the attempt to teach apes human language is an example of what a huge difference it can make, if we free ourselves from a picture that prevents us from seeing the possibility of other pictures.

Attempts to teach apes human language were based on the first picture, which highlights the difference between the one who inspires and the one who is inspired. It was thought that because apes lack the language skills that we humans have, there is only one way to teach apes human language. We need to transfer the language skills horizontally to the apes, by training them. This “single” opportunity failed so clearly, and the failure was so well-documented, that only a few researchers were subsequently open to the results of a markedly more successful, at least as well-documented experiment, which was based on the alternative picture of inspiration.

In the alternative experiment, the researchers saw an opportunity that the first picture made it difficult to see. If apes and humans live together daily in a closely united group, so that they have opportunities to sense affinities with each other, then language seeds that we did not know existed in apes could be inspired to sprout and grow spontaneously in the apes themselves. Vertically within the apes, rather than through horizontal transmission, as when humans train animals. In fact, this alternative experiment was so successful that it resulted in a series of spontaneous language growths in apes. As time went on, new-born apes were inspired not only by the humans in the group, but also by the older apes whose linguistic creativity had taken shape.

If you want to read more about this unexpected possibility of inspiration between species, which suggests unexpected affinities, as when humans are inspired by each other, you will find a book reference below. I wrote the book a long time ago with William M. Fields and Sue Savage-Rumbaugh. Both have inspired me – for which I am deeply grateful – for example, in this blog post with its alternative picture of inspiration. That I mention the book again is because I hope that the time is ripe for philosophers, psychologists, anthropologists, educationalists, linguists, neuroscientists and many others to be inspired by the unexpected possibility of human-inspired linguistic creativity in our non-human relatives.

To finally connect the threads of music and ape language research, I can tell you that two great musicians, Paul McCartney and Peter Gabriel, have visited the language-inspired apes. Both of them played music with the apes and Peter Gabriel and Panbanisha even created a song together. Can we live without inspiration?

Pär Segerdahl

Written by…

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

Segerdahl, P., Fields, W. & Savage-Rumbaugh, S. 2005. Kanzi’s Primal Language. The Cultural Initiation of Primates into Language. Palgrave Macmillan

Segerdahl, P. 2017. Can an Ape Become Your Co-Author? Reflections on Becoming as a Presupposition of Teaching. In: A Companion to Wittgenstein on Education. Pedagogical Investigations. Peters, M. A. and Stickney, J. (Eds.). Singapore: Springer, pp. 539-553

This post in Swedish

We write about apes

Brain-inspired AI: human narcissism again?

This is an age when Artificial Intelligence (AI) is literally exploding and invading almost every aspect of our lives. From entertainment to work, from economics to medicine, from education to marketing, we deal with a number of disparate AI systems that make our lives much easier than a few years ago, but also raise new ethical issues or emphasize old, still open questions.

A basic fact about AI is that it is progressing at an impressive pace, while still being limited with regard to various specific contexts and goals. We often read, also in non-specialized journals, that AI systems are not robust (meaning they are not good at dealing with datasets too much different from the one they have been trained with, so that the risk of cyber-attacks is still pretty high), not fully transparent, and limited in their capacity to generalize, for instance. This suggests that the reliability of AI systems, in other words the possibility to use them for achieving different goals, is limited, and we should not blindly trust them.

A strategy increasingly chosen by AI researchers in order to improve the systems they develop is taking inspiration from biology, and specifically from the human brain. Actually, this is not really new: already the first wave of AI took inspiration from the brain, which was (and still is) the most familiar intelligent system in the world. This trend towards brain-inspired AI is gaining much more momentum today, for two main reasons among others: big data and the very powerful technology to handle big data. And yet, brain-inspired AI raises a number of questions of an even deeper nature, which urge us to stop and think.

Indeed, when compared to the human brain, present AI reveals several differences and limitations with regards to different contexts and goals. For instance, present Machine Learning cannot generalize the abilities it achieves on the basis of specific data in order to use them in different settings and for different goals. Also, AI systems are fragile: a slight change in the characteristics of processed data can have catastrophic consequences. These limitations are arguably dependent on both how AI is conceived (technically speaking: on its underlying architecture), and on how it works (on its underlying technology). I would like to introduce some reflections about the choice to use the human brain as a model for improving AI, including the apparent limitations of this choice to use the brain as a model.

Very roughly, AI researchers are looking at the human brain to infer operational principles and then translate them into AI systems and eventually make these systems better in a number of tasks. But is a brain-inspired strategy the best we can choose? What justifies it? In fact, there are already AI systems that work in ways that do not conform to the human brain. We cannot exclude a priori that AI will eventually develop more successfully along lines that do not fully conform to, or that even deviate from, the way the human brain works.

Also, we should not forget that there is no such thing as the brain: there is a huge diversity both among different people and within the brain itself. The development of our brains reflects a complex interplay between our genetic make-up and our life experiences. Moreover, the brain is a multilevel organ with different structural and functional levels.

Thus, claiming a brain-inspired AI without clarifying which specific brain model is used as a reference (for instance, the neurons’ action potentials rather than the connectomes’ network) is possibly misleading if not nonsensical.

There is also a more fundamental philosophical point worth considering. Postulating that the human brain is paradigmatic for AI risks to implicitly endorse a form of anthropocentrism and anthropomorphism, which are both evidence of our intellectual self-centeredness and of our limited ability to think beyond what we think we are.

While pragmatic reasons might justify the choice to take the brain as a model for AI (after all, for many aspects, the brain is the most efficient intelligent system that we know in nature), I think we should avoid the risk of translating this legitimate technical effort into a further narcissistic, self-referential anthropological model. Our history is already full of such models, and they have not been ethically or politically harmless.

Written by…

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

Approaching future issues

Conceptual analysis when we get stuck in thoughts

When philosophers are asked what method we use when we philosophize, we are happy to answer: our most important method is conceptual analysis. We apply conceptual analysis to answer philosophical questions such as “What is knowledge?”, “What is justice?”, “What is truth?” What we do is that we propose general definitions of the concepts, which we then fine-tune by using concrete examples to test that the definitions really capture all individual cases of the concepts and only these.

The problem is that both those who ask for the method of philosophy and those who answer “conceptual analysis” seem to assume that philosophy is not challenged by deeply disturbing problems, but defines concepts almost routinely. The general questions above are hardly even questions, other than purely grammatically. Who lies awake wondering “What is knowledge, what is justice, what is truth, what is goodness, what is…?”

In order to get insomnia from the questions, in order for the questions to become living philosophical problems, in order for us to be disturbed by them, we need more than only generally formulated questions.

Moreover, if there was such a thing as a method of answering philosophical questions, then the questions should already have been answered. I mean, if we since the days of Socrates had a method that answers philosophical “What is?”-questions by defining concepts, then there cannot be many questions left to answer. At most, we can refine the definitions, or apply the method to concepts that did not exist 2600 years ago. Basically, philosophy should not have many questions left to be challenged by. Since ancient times, we have a well-proven method!

To understand why philosophers continue to wonder, we need to understand why questions that superficially sound so uninteresting that we fall asleep can sometimes be so deeply perplexing that we lie awake thinking. Let me give you an example that gives a glimpse of the depths of philosophy, a glimpse of that disturbing “extra” that keeps philosophers awake at night.

The example is a “Swedish” disease, which has attracted attention around the world as something very strange. I am thinking of what was first called apathy in refugee children, but which later got the name resignation syndrome. The disease affects certain groups of children seeking asylum in Sweden. Children from the former Yugoslavia and from Central Asian countries of the former Soviet Union have been overrepresented. The children lose physical and mental functions and in the end can neither move nor communicate. They become bedridden, do not respond to pain and must be fed by tube. More than 1000 children have been affected by the disease in Sweden since the 1990s.

Confronted with this disease in refugee children, it may seem natural to think that the condition is reasonably caused by traumatic experiences in the home country and during the flight, as well as by the stress of living under deportation threat. It is not unreasonable to think so. Trauma and stress probably contribute to the disease. There is only one problem. If this were the cause, then resignation syndrome should occur in refugee children in other parts of the world as well. Unfortunately, refugee children with traumatic experiences and stressful deportation threats are not only found in Sweden. So why are (certain groups of) refugee children affected by the syndrome in Sweden in particular?

What is resignation syndrome? Here we have a question that on the surface does not sound more challenging than any other generally formulated “What is?”-question. But the question is today a challenging philosophical problem, at least for Karl Sallin, who is writing his dissertation on the syndrome here at CRB, within the framework of the Human Brain Project. What is that “extra” element that makes the question philosophically challenging for Karl Sallin?

It may seem natural to think that the challenging aspect of the question is simply that we do not yet know the answer. We do not know all the facts. It is not unreasonable to think so. Lack of knowledge naturally contributes to the question. Again, there is only one problem. We already consider ourselves knowing the answer! We think that this extreme form of despair in refugee children must, of course, be caused by traumatic experiences and by the stress that the threat of deportation entails. In the end, they can no longer bear it, but give up! If this reasonable answer were correct, then resignation syndrome should not exist only in Sweden. The philosophical question thus arises because the only reasonable answer conflicts with obvious facts.

That is why the question is philosophically challenging. Not because we do not know the answer. But because we consider ourselves to know what the answer must be! The answer seems so reasonable that we should hardly need to do more research on the matter before we take action by alleviating the children’s stressful situation, which we think is the only possible cause of the syndrome. And that is what happened…

For some years now, the guidelines for Swedish health care staff have emphasized the family’s role in recovery, as well as the importance of working for a residence permit. The guidelines are governed by the seemingly reasonable idea that children’s recovery depends on relieving the stress that causes the syndrome. Once again, there is only one problem. The guidelines never had a positive effect on the syndrome, despite attempts to create peace and stability in the family and work for a residence permit. The syndrome continued to be a “Swedish” disease. Why is the condition so stubbornly linked to Sweden?

Do you see the philosophical problem? It is not just about lack of knowledge. It is about the fact that we already think we have knowledge. The thought that the cause must be stress is so obvious, that we hardly notice that we are thinking it. It seems immediately real. In short, we have got stuck in our own thoughts, which we repeat again and again, even though we repeatedly clash with obvious facts. Like a mosquito trying to get out of a window, but just crashing, crashing, crashing.

When Karl Sallin treats the issue of resignation syndrome as a philosophical issue, he does something extremely unusual, for which there are no routine methods. He directs his attention not only outwards towards the disease, but also inwards towards ourselves. More empirical research alone does not solve the problem. As little as continuing to collide with the glass pane solves the mosquito’s problem. We need to stop and examine ourselves.

This post has now become so long that I have to stop before I can describe Karl Sallin’s dissolution of the mystery. Maybe it is good that we are not rushing forward. Riddles need time, which our impatient intellect rarely gives them. The point about the method of philosophy has hopefully become clear. The reason why philosophers analyse concepts is that we humans sometimes get caught up in our own concepts of reality. In this case, we get stuck in our concept of resignation syndrome as a stress disorder. Perhaps I can still mention that Karl Sallin’s conceptual analysis of our thought pattern about the syndrome dissolves the feeling of being faced with an incomprehensible mystery. The syndrome is no longer in conflict with obvious facts. He also shows that our thought patterns may have contributed to the disease becoming so prominent in Sweden. Our publically stated belief that the disease must be caused by stress, and our attempts to cure the disease by relieving stress, created a cultural context where this “Swedish” disease became possible. The cultural context affected the mind and the brain, which affected the biology of the body. In any case, that is what Karl Sallin suggests: resignation syndrome is a culture-bound disease. This unexpected possibility frees us from the thought we were stuck in as the only alternative.

So why did Socrates ask questions in Athens 2600 years ago? Because he discovered a method that could answer philosophical questions? My guess is that he did it for the same reason that Karl Sallin does it today. Because we humans have a tendency to imagine that we already know the answers. When we clearly see that we do not know what we thought we knew, we are freed from repeatedly colliding with a reality that should be obvious.

In philosophy, it is often the answer that is the question.

Pär Segerdahl

Written by…

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

Sallin, K., Evers, K., Jarbin, H., Joelsson, L., Petrovic, P. (2021) Separation and not Residency Permit Restores Function in Resignation Syndrome: A Retrospective Cohort Study. Eur Child Adolesc Psychiatry, 10.1007/s00787-021-01833-3

Sallin, K., Lagercrantz, H., Evers, K., Engström, I., Hjern, A., Petrovic, P. (2016) Resignation Syndrome: Catatonia? Culture-Bound? Frontiers in Behavioral Neuroscience, 10:7. 10.3389/fnbeh.2016.00007

This post in Swedish

We challenge habits of thought

Philosophical research communication

How do you communicate about research with people who are not researchers? The scientific results usually presuppose a complicated intellectual framework, which the researchers have acquired through long education and experience. How can we talk about their research with people who are not researchers?

At CRB, we take research communication seriously, so this question follows us daily. A common way to solve the problem is to replace researchers’ complex intellectual frameworks with simple images, which people in general are more familiar with. An example could be comparing a body cell with a small factory. We thus compare the unknown with the familiar, so that the reader gets a certain understanding: “Aha, the cell functions as a kind of factory.”

Giving research results a more comprehensible context by using images that replace the researchers’ intellectual framework often works well. We sometimes use that method ourselves here at CRB. But we also use another way of embedding the research, so that it touches people. We use philosophical reflection. We ask questions that you do not need to be an expert to wonder about. The questions lead to thoughts that you do not need to be a specialist to follow. Finally, the research results are incorporated into the reasoning. We then point out that a new article sheds light on the issues we have thought about together. In this way, the research gets an understandable context, namely, in the form of thoughts that anyone can have.

We could call this philosophical research communication. There is a significant difference between these two ways of making research understandable. When simple images are used, they only aim to make people (feel that they) understand what they are not familiar with. The images are interchangeable. If you find a better image, you immediately use it instead. The images are not essential in themselves. That we compare the body cell with a factory does not express any deep interest in factories. But the philosophical questions and reflections that we at CRB embed the research in, are essential in themselves. They are sincere questions and thoughts. They cannot be replaced by other questions and reasoning, for the sole purpose of effectively conveying research results. In philosophical research communication, we give research an essential context, which is not just an interchangeable pedagogical aid. The embedding is as important as what is embedded.

Philosophical research communication is particularly important to us at CRB, as we are a centre for ethics research. Our research is driven by philosophical questions and reflections, for example, within the Human Brain Project, which examines puzzling phenomena such as consciousness and artificial intelligence. Even when we perform empirical studies, the point of those studies is to shed light on ethical problems and thoughts. In our research communication, we focus on this interplay between the philosophically thought-provoking and the empirical results.

Another difference between these ways of communicating research has to do with equality. Since the simple images that are used to explain research are not essential in themselves, such research communication is, after all, somewhat unequal. The comparison, which seemed to make us equal, is not what the communication is really about. The reader’s acquaintance with factories does not help the reader to have their own views on research. Philosophical research communication is different. Because the embedding philosophical questions and thoughts are essential and meant seriously, we meet on the same level. We can wonder together about the same honest questions. When research is communicated philosophically, communicators as well as researchers and non-researchers are equal.

Philosophical research communication can thereby deepen the meaning of the research, sometimes even for the researchers themselves!

As philosophical research communication unites us around common questions and thoughts, it is important in an increasingly fragmented and specialized society. It helps us to think together, which is easier than you might believe, if we dare to open up to our own questions. Here, of course, I assume that the communication is sincere, that it comes from independently thinking people, that it is not based on any intellectually constructed thought patterns, which one must be a philosophy expert to understand.

In that case, philosophical research communicators would need to bring philosophy itself to life, by sincerely asking the most alive questions.

Pär Segerdahl

Written by…

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

This post in Swedish

We care about communication

« Older posts