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

Tag: Artificial Intelligence (Page 3 of 3)

Ethical fitness apps for high performance morality

In an unusually rhetorical article for being in a scientific journal, the image is drawn of a humanity that frees itself from moral weakness by downloading ethical fitness apps.

The authors claim that the maxim “Know thyself!” from the temple of Apollo at Delphi is answered today more thoroughly than ever. Never has humanity known more about itself. Ethically, we are almost fully educated. We also know more than ever about the moral weaknesses that prevent us from acting in accordance with the ethical principles that we finally know so well. Research is discovering more and more mechanisms in the brain and in our psychology that affect humanity’s moral shortcomings.

Given this enormous and growing self-knowledge, why do we not develop artificial intelligence that supports a morally limping humanity? Why spend so much resources on developing even more intelligent artificial intelligence, which takes our jobs and might one day threaten humanity in the form of uncontrollable superintelligence? Why do we behave so unwisely when we could develop artificial intelligence to help us humans become superethical?

How can AI make morally weak humans super-ethical? The authors suggest a comparison with the fitness apps that help people to exercise more efficiently and regularly than they otherwise would. The authors’ suggestion is that our ethical knowledge of moral theories, combined with our growing scientific knowledge of moral weaknesses, can support the technological development of moral crutches: wise objects that support people precisely where we know that we are morally limping.

My personal assessment of this utopian proposal is that it might easily be realized in less utopian form. AI is already widely used as a support in decision-making. One could imagine mobile apps that support consumers to make ethical food choices in the grocery shop. Or computer games where consumers are trained to weigh different ethical considerations against each another, such as animal welfare, climate effects, ecological effects and much more. Nice looking presentations of the issues and encouraging music that make it fun to be moral.

The philosophical question I ask is whether such artificial decision support in shops and other situations really can be said to make humanity wiser and more ethical. Imagine a consumer who chooses among the vegetables, eagerly looking for decision support in the smartphone. What do you see? A human who, thanks to the mobile app, has become wiser than Socrates, who lived long before we knew as much about ourselves as we do today?

Ethical fitness apps are conceivable. However, the risk is that they spread a form of self-knowledge that flies above ourselves: self-knowledge suspiciously similar to the moral vice of self-satisfied presumptuousness.

Pär Segerdahl

Written by…

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

Pim Haselager & Giulio Mecacci (2020) Superethics Instead of Superintelligence: Know Thyself, and Apply Science Accordingly, AJOB Neuroscience, 11:2, 113-119, DOI: 10.1080/21507740.2020.1740353

The temptation of rhetoric

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Responsibly planned research communication

Academic research is driven by dissemination of results to peers at conferences and through publication in scientific journals. However, research results belong not only to the research community. They also belong to society. Therefore, results should reach not only your colleagues in the field or the specialists in adjacent fields. They should also reach outside the academy.

Who is out there? A homogeneous public? No, it is not that simple. Communicating research is not two activities: first communicating the science to peers and then telling the popular scientific story to the public. Outside the academy, we find engineers, entrepreneurs, politicians, government officials, teachers, students, research funders, taxpayers, healthcare professionals… We are all out there with our different experiences, functions and skills.

Research communication is therefore a strategically more complicated task than just “reaching the public.” Why do you want to communicate your results; why are they important? Who will find your results important? How do you want to communicate them? When is the best time to communicate? There is not just one task here. You have to think through what the task is in each particular case. For the task varies with the answers to these questions. Only when you can think strategically about the task can you communicate research responsibly.

Josepine Fernow is a skilled and experienced research communications officer at CRB. She works with communication in several research projects, including the Human Brain Project and STARBIOS2. In the latter project, about Responsible Research and Innovation (RRI), she contributes in a new book with arguments for responsibly planned research communication: Achieving impact: some arguments for designing a communications strategy.

Josepine Fernow’s contribution is, in my view, more than a convincing argument. It is an eye-opening text that helps researchers see more clearly their diverse relationships to society, and thereby their responsibilities. The academy is not a rock of knowledge in a sea of ​​ignorant lay people. Society consists of experienced people who, because of what they know, can benefit from your research. It is easier to think strategically about research communication when you survey your relations to a diversified society that is already knowledgeable. Josepine Fernow’s argumentation helps and motivates you to do that.

Josepine Fernow also warns against exaggerating the significance of your results. Bioscience has potential to give us effective treatments for serious diseases, new crops that meet specific demands, and much more. Since we are all potential beneficiaries of such research, as future patients and consumers, we may want to believe the excessively wishful stories that some excessively ambitious researchers want to tell. We participate in a dangerous game of increasingly unrealistic hopes.

The name of this dangerous game is hype. Research hype can make it difficult for you to continue your research in the future, because of eroded trust. It can also make you prone to take unethical shortcuts. The “huge potential benefit” obscures your judgment as a responsible researcher.

In some research fields, it is extra difficult to avoid research hype, as exaggerated hopes seem inscribed in the very language of the field. An example is artificial intelligence (AI), where the use of psychological and neuroscientific vocabulary about machines can create the impression that one has already fulfilled the hopes. Anthropomorphic language can make it sound as if some machines already thought like humans and functioned like brains.

Responsible research communication is as important as difficult. Therefore, these tasks deserve our greatest attention. Read Josepine Fernow’s argumentation for carefully planned communication strategies. It will help you see more clearly your responsibility.

Finally, a reminder for those interested: the STARBIOS2 project organizes its final event via Zoom on Friday, May 29, 2020.

Pär Segerdahl

Written by…

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

Fernow, J. (2019). Note #11: Achieving impact: Some arguments for designing a communications strategy, In A. Declich (Ed.), RRI implementation in bioscience organisations: Guidelines from the STARBIOS2 project, (pp. 177-180). Uppsala University. ISBN: 978-91-506-2811-1

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Anthropomorphism in AI can limit scientific and technological development

Anthropomorphism almost seems inscribed in research on artificial intelligence (AI). Ever since the beginning of the field, machines have been portrayed in terms that normally describe human abilities, such as understanding and learning. The emphasis is on similarities between humans and machines, while differences are downplayed. Like when it is claimed that machines can perform the same psychological tasks that humans perform, such as making decisions and solving problems, with the supposedly insignificant difference that machines do it “automated.”

You can read more about this in an enlightening discussion of anthropomorphism in and around AI, written by Arleen Salles, Kathinka Evers and Michele Farisco, all at CRB and the Human Brain Project. The article is published in AJOB Neuroscience.

The article draws particular attention to so-called brain-inspired AI research, where technology development draws inspiration from what we know about the functioning of the brain. Here, close relationships are emphasized between AI and neuroscience: bonds that are considered to be decisive for developments in both fields of research. Neuroscience needs inspiration from AI research it is claimed, just as AI research needs inspiration from brain research.

The article warns that this idea of ​​a close relationship between the two fields presupposes an anthropomorphic interpretation of AI. In fact, brain-inspired AI multiplies the conceptual double exposures by projecting not only psychological but also neuroscientific concepts onto machines. AI researchers talk about artificial neurons, synapses and neural networks in computers, as if they incorporated artificial brain tissue into the machines.

An overlooked risk of anthropomorphism in AI, according to the authors, is that it can conceal essential characteristics of the technology that make it fundamentally different from human intelligence. In fact, anthropomorphism risks limiting scientific and technological development in AI, since it binds AI to the human brain as privileged source of inspiration. Anthropomorphism can also entice brain research to uncritically use AI as a model for how the brain works.

Of course, the authors do not deny that AI and neuroscience mutually support each other and should cooperate. However, in order for cooperation to work well, and not limit scientific and technological development, philosophical thinking is also needed. We need to clarify conceptual differences between humans and machines, brains and computers. We need to free ourselves from the tendency to exaggerate similarities, which can be more verbal than real. We also need to pay attention to deep-rooted differences between humans and machines, and learn from the differences.

Anthropomorphism in AI risks encouraging irresponsible research communication, the authors further write. This is because exaggerated hopes (hype) seem intrinsic to the anthropomorphic language. By talking about computers in psychological and neurological terms, it sounds as if these machines already essentially functioned as human brains. The authors speak of an anthropomorphic hype around neural network algorithms.

Philosophy can thus also contribute to responsible research communication about artificial intelligence. Such communication draws attention to exaggerated claims and hopes inscribed in the anthropomorphic language of the field. It counteracts the tendency to exaggerate similarities between humans and machines, which rarely go as deep as the projected words make it sound.

In short, differences can be as important and instructive as similarities. Not only in philosophy, but also in science, technology and responsible research communication.

Pär Segerdahl

Written by…

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

Arleen Salles, Kathinka Evers & Michele Farisco (2020) Anthropomorphism in AI, AJOB Neuroscience, 11:2, 88-95, DOI: 10.1080/21507740.2020.1740350

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What is a moral machine?

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

Written by…

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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Artificial intelligence and living consciousness

The Ethics Blog will publish several posts on artificial intelligence in the future. Today, I just want to make a little observation of something remarkable.

The last century was marked by fear of human consciousness. Our mind seemed as mystic as the soul, as superfluous in a scientific age as God. In psychology, behaviorism flourished, which defined psychological words in terms of bodily behavior that could be studied scientifically in the laboratory. Our living consciousness was treated as a relic from bygone superstitious ages.

What is so remarkable about artificial intelligence? Suddenly, one seems to idolize consciousness. One wallows in previously sinful psychological words, at least when one talks about what computers and robots can do. These machines can see and hear; they can think and speak. They can even learn by themselves.

Does this mean that the fear of consciousness has ceased? Hardly, because when artificial intelligence employs psychological words such as seeing and hearing, thinking and understanding, the words cease to be psychological. The idea of computer “learning,” for example, is a technical term that computer experts define in their laboratories.

When artificial intelligence embellishes machines with psychological words, then, one repeats how behaviorism defined mind in terms of something else. Psychological words take on new machine meanings that overshadow the meanings the words have among living human beings.

Remember this next time you wonder if robots might become conscious. The development exhibits fear of consciousness. Therefore, what you are wondering is not if robots can become conscious. You wonder if your own consciousness can be superstition. Remarkable, right?

Pär Segerdahl

Written by…

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

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How can we set future ethical standards for ICT, Big Data, AI and robotics?

josepine-fernow-siennaDo you use Google Maps to navigate in a new city? Ask Siri, Alexa or OK Google to play your favourite song? To help you find something on Amazon? To read a text message from a friend while you are driving your car? Perhaps your car is fitted with a semi-autonomous adaptive cruise control system… If any software or machine is going to perform in any autonomous way, it needs to collect data. About you, where you are going, what songs you like, your shopping habits, who your friends are and what you talk about. This begs the question:  are we willing to give up part of our privacy and personal liberty to enjoy the benefits technology offers.

It is difficult to predict the consequences of developing and using new technology. Policymakers struggle to assess the ethical, legal and human rights impacts of using different kinds of IT systems. In research, in industry and our homes. Good policy should be helpful for everyone that holds a stake. We might want it to protect ethical values and human rights, make research and development possible, allow technology transfer from academia to industry, make sure both large and smaller companies can develop their business, and make sure that there is social acceptance for technological development.

The European Union is serious about developing policy on the basis of sound research, rigorous empirical data and wide stakeholder consultation. In recent years, the Horizon2020 programme has invested € 10 million in three projects looking at the ethics and human rights implications of emerging digital technologies: PANELFIT, SHERPA and SIENNA.

The first project, PANELFIT (which is short for Participatory Approaches to a New Ethical and Legal Framework for ICT), will develop guidelines on the ethical and legal issues of ICT research and innovation. The second, SHERPA (stands for Shaping the ethical dimensions of Smart Information Systems (SIS) – A European Perspective), will develop tools to identify and address the ethical dimensions of smart information systems (SIS), which is the combination of artificial intelligence (AI) and big data analytics. SIENNA (short for Stakeholder-informed ethics for new technologies with high socio-economic and human rights impact), will develop research ethics protocols, professional ethical codes, and better ethical and legal frameworks for AI and robotics, human enhancement technologies, and human genomics.

SSP-graphic

All three projects involve experts, publics and stakeholders to co-create outputs, in different ways. They also support the European Union’s vision of Responsible Research and Innovation (RRI). SIENNA, SHERPA and PANELFIT recently published an editorial in the Orbit Journal, inviting stakeholders and publics to engage with the projects and contribute to the work.

Want to read more? Rowena Rodrigues and Anaïs Resseguier have written about some of the issues raised by the use of artificial intelligence on Ethics Dialogues (The underdog in the AI and ethical debate: human autonomy), and you can find out more about the SIENNA project in a previous post on the Ethics Blog (Ethics, human rights and responsible innovation).

Want to know more about the collaboration between SIENNA, SHERPA and PANELFIT? Read the editorial in Orbit (Setting future ethical standards for ICT, Big Data, AI and robotics: The contribution of three European Projects), or watch a video from our joint webinar on May 20, 2019 on YouTube (SIENNA, SHERPA, PANELFIT: Setting future ethical standards for ICT, Big Data, SIS, AI & Robotics).

Want to know how SIENNA views the ethical impacts of AI and robotics? Download infographic (pdf) and read our state-of-the-art review for AI & robotics (deliverable report).

AI-robotics-ifographic

Josepine Fernow

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Driverless car ethics

Pär SegerdahlSelf-driving robot cars are controlled by computer programs with huge amounts of traffic rules. But in traffic, not everything happens smoothly according to the rules. Suddenly a child runs out on the road. Two people try to help a cyclist who collapsed on the road. A motorist tries to make a U-turn on a too narrow road and is stuck, blocking the traffic.

Assuming that the robots’ programs are able to categorize traffic situations through image information from the cars’ cameras, the programs must select the appropriate driving behavior for the robot cars. Should the cars override important traffic rules by, for example, steering onto the sidewalk?

It is more complicated than that. Suppose that an adult is standing on the sidewalk. Should the adult’s life be compromised to save the child? Or to save the cyclist and the two helpful persons?

The designers of self-driving cars have a difficult task. They must program the cars’ choice of driving behavior in ethically complex situations that we call unexpected, but the engineers have to anticipate far in advance. They must already at the factory determine how the car model will behave in future “unexpected” traffic situations. Maybe ten years later. (I assume the software is not updated, but also updated software anticipates what we normally see as unexpected events.)

On a societal level, one now tries to agree on ethical guidelines for how future robot cars should behave in tragic traffic situations where it may not be possible to completely avoid injuries or fatal casualties. A commission initiated by the German Ministry for Transportation, for example, suggests that passengers of robot cars should never be sacrificed to save a larger number of lives in the traffic situation.

Who, by the way, would buy a robot car that is programmed to sacrifice one’s life? Who would choose such a driverless taxi? Yet, as drivers we may be prepared to sacrifice ourselves in unexpected traffic situations. Some researchers decided to investigate the matter. You can read about their study in ScienceDaily, or read the research article in Frontiers in Behavioral Neuroscience.

The researchers used Virtual Reality (VR) technology to expose subjects to ethically difficult traffic situations. Thereafter, they studied the subjects’ choice of traffic behavior. The researchers found that the subjects were surprisingly willing to sacrifice themselves to save others. But they also took into consideration the age of potential victims and were prepared to steer onto the sidewalk to minimize the number of traffic victims. This is contrary to norms that we hold important in society, such as the idea that age discrimination should not occur and that the lives of innocent people should be protected.

In short, humans are inclined to drive their cars politically incorrectly!

Why was the study done? As far as I understand, because the current discussion about ethical guidelines does not take into account empirical data on how living drivers are inclined to drive their cars in ethically difficult traffic situations. The robot cars will make ethical decisions that can make the owners of the cars dissatisfied with their cars; morally dissatisfied!

The researchers do not advocate that driverless cars should respond to ethically complex traffic situations as living people do. However, the discussion about driverless car ethics should take into account data on how living people are inclined to drive their cars in traffic situations where it may not be possible to avoid accidents.

Let me complement the empirical study with some philosophical reflections. What strikes me when I read about driverless car ethics is that “the unexpected” disappears as a living reality. A living driver who tries to handle a sudden traffic situation manages what very obviously is happening right now. The driverless car, on the other hand, takes decisions that tick automatically, as predetermined as any other decision, like stopping at a red light. Driverless car ethics is just additional software that the robot car is equipped with at the factory (or when updating the software).

What are the consequences?

A living driver who suddenly ends up in a difficult traffic situation is confronted – as I said – with what is happening right now. The driver may have to bear responsibility for his actions in this intense moment during the rest of his life. Even if the driver rationally sacrifices one life to save ten, the driver will bear the burden of this one death; dream about it, think about it. And if the driver makes a stupid decision that takes more lives than it saves, it may still be possible to reconcile with it, because the situation was so unexpected.

This does not apply, however, to the robot car that was programmed at the factory according to guidelines from the National Road Administration. We might want to say that the robot car was preprogrammed to sacrifice our sister’s life, when she stood innocently on the sidewalk. Had the car been driven by a living person, we would have been angry with the driver. But after some time, we might be able to start reconciling with the driver’s behavior. Because it was such an unexpected situation. And the driver is suffering from his actions.

However, if it had been a driverless car that worked perfectly according to the manufacturer’s programs and the authorities’ recommendations, then we might see it as a scandal that the car was preprogrammed to steer onto the sidewalk, where our sister stood.

One argument for driverless cars is that, by minimizing the human factor, they can reduce the number of traffic accidents. Perhaps they can. But maybe we are less accepting as to how they are programmed to save lives in ethically difficult situations. Not only are they preprogrammed so that “the unexpected” disappears as a reality. They do not bear the responsibility that living people are forced to bear, even for their rational decisions.

Well, we will probably find ways to implement and accept the use of driverless cars. But another question still concerns me. If the present moment disappears as a living reality in the ethics software of driverless cars, has it not already disappeared in the ethics that prescribes right and wrong for us living people?

Pär Segerdahl

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Prepare for robot nonsense

Pär SegerdahlAs computers and robots take over tasks that so far only humans could carry out, such as driving a car, we are likely to experience increasingly insidious uses of language by the technology’s intellectual clergy.

The idea of ​​intelligent computers and conscious robots is for some reason terribly fascinating. We see ourselves as intelligent and conscious beings. Imagine if also robots could be intelligent and aware! In fact, we have already seen them (almost): on the movie screen. Soon we may see them in reality too!

Imagine that artifacts that we always considered dead and mechanical one day acquired the enigmatic character of life! Imagine that we created intelligent life! Do we have enough exclamation marks for such a miracle?

The idea of ​​intelligent life in supercomputers often comes with the idea of a test that can determine if a supercomputer is intelligent. It is as if I wanted to make the idea of ​​perpetual motion machines credible by talking about a perpetuum mobile test, invented by a super-smart mathematician in the 17th century. The question if something is a perpetuum mobile is determinable and therefore worth considering! Soon they may function as engines in our intelligent, robot-driven cars!

There is a famous idea of ​​an intelligence test for computers, invented by the British mathematician, Alan Turing. The test allegedly can determine whether a machine “has what we have”: intelligence. How does the test work? Roughly, it is about whether you can distinguish a computer from a human – or cannot do it.

But distinguishing a computer from a human being surely is no great matter! Oh, I forgot to mention that there is a smoke screen in the test. You neither see, hear, feel, taste nor smell anything! In principle, you send written questions into the thick smoke. Out of the smoke comes written responses. But who wrote/generated the answers? Human or computer? If you cannot distinguish the computer-generated answers from human answers – well, then you had better take protection, because an intelligent supercomputer hides behind the smoke screen!

The test is thus adapted to the computer, which cannot have intelligent facial expressions or look perplexed, and cannot groan, “Oh no, what a stupid question!” The test is adapted to an engineer’s concept of intelligent handling of written symbol sequences. The fact that the test subject is a poor human being who cannot always say who/what “generated” the written answers hides this conceptual fact.

These insidious linguistic shifts are unusually obvious in an article I encountered through a rather smart search engine. The article asks if machines can be aware. And it responds: Yes, and a new Turing test can prove it.

The article begins with celebrating our amazing consciousness as “the ineffable and enigmatic inner life of the mind.” Consciousness is then exemplified by the whirl of thought and sensation that blossoms within us when we finally meet a loved one again, hear an exquisite violin solo, or relish an incredible meal.

After this ecstatic celebration of consciousness, the concept begins to be adapted to computer engineering so that finally it is merely a concept of information processing. The authors “show” that consciousness does not require interaction with the environment. Neither does it require memories. Consciousness does not require any emotions like anger, fear or joy. It does not require attention, self-reflection, language or ability to act in the world.

What then remains of consciousness, which the authors initially made it seem so amazing to possess? The answer in the article is that consciousness has to do with “the amount of integrated information that an organism, or a machine, can generate.”

The concept of consciousness is gradually adapted to what was to be proven. Finally, it becomes a feature that unsurprisingly can characterize a computer. After we swallowed the adaptation, the idea is that we, at the Grand Finale of the article, should once again marvel, and be amazed that a machine can have this “mysterious inner life” that we have, consciousness: “Oh, what an exquisite violin solo, not to mention the snails, how lovely to meet again like this!”

The new Turing test that the authors imagine is, as far as I understand, a kind of picture recognition test: Can a computer identify the content of a picture as “a robbery”? A conscious computer should be able to identify pictorial content as well as a human being can do it. I guess the idea is that the task requires very, very much integrated information. No simple rule of thumb, man + gun + building + terrified customer = robbery, will do the trick. It has to be such an enormous amount of integrated information that the computer simply “gets it” and understands that it is a robbery (and not a five-year-old who plays with a toy gun).

Believing in the test thus assumes that we swallowed the adapted concept of consciousness and are ecstatically amazed by super-large amounts of integrated information as: “the ineffable and enigmatic inner life of the mind.”

These kinds of insidious linguistic shifts will attract us even more deeply as robotics develop. Imagine an android with facial expression and voice that can express intelligence or groan at stupid questions. Then surely, we are dealing an intelligent and conscious machine!

Or just another deceitful smoke screen; a walking, interactive movie screen?

Pär Segerdahl

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Ethics, human rights and responsible innovation

josepine-fernow2It is difficult to predict the consequences of developing and using new technologies. We interact with smart devices and intelligent software on an almost daily basis. Some of us use prosthetics and implants to go about our business and most of us will likely live to see self-driving cars. In the meantime, Swedish research shows that petting robot cats looks promising in the care of patients with dementia. Genetic tests are cheaper than ever, and available to both patients and consumers. If you spit in a tube and mail it to a US company, they will tell you where your ancestors are from. Who knows? You could be part sub Saharan African, and part Scandinavian at the same time, and (likely) still be you.

Technologies, new and old, have both ethical and human rights impact. Today, we are closer to scenarios we only pictured in science fiction a few decades ago. Technology develops fast and it is difficult to predict what is on the horizon. The legislation, regulation and ethical guidance we have today was developed for a different future. Policy makers struggle to assess the ethical, legal and human rights impact of new and emerging technologies. These frameworks are challenged when a country like Saudi Arabia, criticized for not giving equal rights to women, offers a robot honorary citizenship. This autumn marks the start of a research initiative that will look at some of these questions. A group of researchers from Europe, Asia, Africa and the Americas join forces to help improve the ethical and legal frameworks we have today.

The SIENNA project (short for Stakeholder-informed ethics for new technologies with high socio-economic and human rights impact) will deliver proposals for professional ethics codes, guidelines for research ethics committees and better regulation in three areas: human genetics and genomics, human enhancement, and artificial intelligence & robotics. The proposals will build on input from stakeholders, experts and citizens. SIENNA will also look at some of the more philosophical questions these technologies raise: Where do we draw the line between health and illness, normality and abnormality? Can we expect intelligent software to be moral? Do we accept giving up some of our privacy to screen our genome for genetic disorders? And if giving up some of our personal liberty is the price we have to pay to interact with machines, are we willing to pay it?

 The project is co-ordinated by the University of Twente. Uppsala University’s Centre for Research Ethics & Bioethics contributes expertise on the ethical, legal and social issues of genetics and genomics, and experience of communicating European research. Visit the SIENNA website at www.sienna-project.eu to find out more about the project and our partners!

Josepine Fernow

The SIENNA projectStakeholder-informed ethics for new technologies with high socio-economic and human rights impact – has received just under € 4 million for a 3,5 year project under the European Union’s H2020 research and innovation programme, grant agreement No 741716.

Disclaimer: This text and its contents reflects only SIENNA’s view. The Commission is not responsible for any use that may be made of the information it contains.

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