Category Archives: Governance

Q & A on AI

Q: Where does AI begin and where does it end?

A: AI will probably have neither beginning nor end, but will be seamlessly integrated into our daily lives, which could mean that in the future we will no longer speak of “artificial” intelligence at all, but only of “smart” or “dumb”. Either we and everything around us, for example, our houses, our cars, our cities etc. are smart or dumb.

Q: How does AI relate to philosophy?

A: At the moment, philosophy is concerned with AI insofar as it can be compared to human intelligence or consciousness. But it is to be suspected that a useful philosophical theory of AI would have to be a philosophy of information. Being “smart” is about the optimal use of information. Information and not cognition, consciousness, or mind is the correct fundamental concept for a philosophy of AI.

Q: When is AI obligatory and when is it voluntary?

A: Obligation and freedom are terms that refer to individual human beings and their position in society. According to modern Western beliefs, one has duties towards society and towards oneself one is free and independent. AI, in this frame of thinking, is seen as something in society that is a threat to freedom for the individual. But as for all social conditions of human existence, i.e., as for all technologies, one must ask whether one can be truly independent and autonomous. After all, when is electricity, driving a car, making a phone call, using a refrigerator, etc. voluntary or mandatory? If technology is society, and an individual outside of society and completely independent of all technology does not exist, then the whole discussion about freedom is of little use. Am I unfree if the self-driving car decides whether I turn right or left? Am I free if I can decide whether I want to stay dumb instead of becoming smart?

Q: What can the status quo be maintained during permanent development?

A: This question is answered everywhere with the term “sustainability”. When it is said that a business, a technology, a school, or a policy should be sustainable, the aim is to maintain a balance under changing conditions. But it is doubtful whether real development can take place within the program of sustainability. Whatever I define as sustainable at the moment, e.g., the stock of certain trees in a forest, can be destructive and harmful under other conditions, e.g., climate change. Sustainability prioritizes stability and opposes change. To value stability in an uncertain, complex, and rapidly changing world is misguided and doomed to failure. We will have to replaced sustainability as a value with a different value. The best candidate could be something like flexibility, i.e., because we cannot or do not want to keep given conditions stable, we will have to make everything optimally changeable.

Q: Who is mainly responsible for AI development in a household?

A: In complex socio-technical systems, all stakeholders bear responsibility simultaneously and equally. Whether this is a household or a nation, it is the stakeholders, both humans and machines, who contribute to the operations of the network and consequently share responsibility for the network. This question is ethically interesting, since in traditional ethics one must always find a “culprit” when something goes wrong. Since ethics, morals, and the law are only called upon the scene and can only intervene when someone does something voluntarily and knowingly that is immoral or illegal, there needs to be a perpetrator. Without a perpetrator, no one can be held ethically or legally accountable. In complex socio-technical systems, e.g., an automated traffic system with many different actors, there is no perpetrator. For this reason, everyone must take responsibility. Of course, there can and must be role distinctions and specializations, but the principle is that the network is the actor and not any actors in the network. Actors, both human and non-human, can only “do” things within the network and as a network.  

Q: Who is primarily responsible for AI use in a household?

A: Same as above

Q: Who is mainly responsible for AI development in a company?

A: Same as above

Q: Who is primarily responsible for AI use in an enterprise?

A: Same as above

Q: Who is primarily responsible for AI development in a community/city?

A: Same as above

Q: Who is primarily responsible for AI use in a community/city?

A: Same as above

Q: Who is primarily responsible for AI development in a country?

A: Same as above

Q: Who is primarily responsible for AI use in a country?

A: Same as above

Q: Can there even be a global regulation on AI?

A: All the questions above reflect our traditional hierarchies and levels of regulation, from household to nation or even the world. What is interesting about socio-technical networks is that they do not follow this hierarchy. They are simultaneously local and global. An AI in a household, for example Alexa, is globally connected and operates because of this global connectivity. If we are going to live in a global network society in the future, then new forms of regulation need to be developed. These new forms of regulation must be able to operate as governance (bottom up and distributed) rather than government, i.e., hierarchical. To develop and implement these new forms of governance is a political task but it is not only political. It is also ethical. For as long as we are guided by values in our laws and rules politics ultimately rest upon what people in a society value. The new values that guide the regulation of a global network society need to be discovered and brought to bear on all the above questions. This is a fitting task for a digital ethics.

Q: Who would develop these regulations?

A: Here again, only all stakeholders in a network can be responsible for setting up regulatory mechanisms and also for control. One could imagine that a governance framework was developed bottom up and that in addition to internal controlling also an external audit would monitor the compliance with the rules. This could be the function of politics in the global network society. There will be no global government, but indeed global governance. The role of government would be to audit the self-organizing governance frameworks of the networks of which society consists.

Q: Should there be an AI driver’s license in the future?

A: The idea of a driver’s license for AI users, like for a car or a computer, assumes that we control the AIs. But what if it is the AIs that are driving us? Would they perhaps have to have a kind of driver’s license certifying their competence for steering humans?

Q: What would the conditions be for that?

A: Whether AIs get a human or social driver’s license that certifies them as socially competent would have to be based on a competence profile of AIs as actors in certain networks. The network constructs the actors, and at the same time is constructed by the actors who integrate into the network. Each network would need to develop the AIs it needs, but also be open to being conditioned as a network by those AIs. This ongoing process is to be understood and realized as governance in the sense described above.

Q: How will society from young to old be sensitized and educated?

A: At the moment, there is much discussion of either “critical thinking” or “media literacy” in this context. Both terms are insufficient and misleading. When critical thinking is mentioned, it is unclear what criticism means. For the most part, it means that one is of the same opinion as those who call for critical thinking. Moreover, it is unclear what is meant by thinking. Critique is everywhere. Everything and everyone is constantly being criticized. But where is the thinking? Again, thinking mostly means thinking like those who say what one should criticize. Since this is different in each case and everyone has their own agenda, the term remains empty and ambiguous. The same is true of the term media literacy. In general, media literacy means knowing how the media select, process and present information, and it also means being aware that this is done not according to criteria of truth-seeking, but criteria of the media business. Knowing this, however, is not a recipe for effectively distinguishing truth from fake news. For that, one needs to know a lot more about how to research for information and how to judge its reliability.

Q: Where do the necessary resources for this come from?

A: There is a tendency to defer the task of education and training to the education system. Schools are supposed to ensure that children grow up with media literacy and the ability to think critically. But how this “training task” is understood and implemented is unclear. Since the school system has largely shown itself to be resistant to criticism in terms of pedagogy and curriculum, and since it still sees certification rather than education as its primary task, the traditional education system cannot be expected to be capable of doing the job that is needed. As in other areas of society, schools will have to transform themselves into networks and learn to deal with information much more flexibly than is the case today. Perhaps schools in their current form will no longer be needed.

Q: Will there ever be effective privacy online?

A: It could also be asked whether there is or could be effective privacy offline. In general, it depends on what one means by privacy. At the moment, privacy or data protection is a code word for the autonomous, rational subject of Western democracy, or in short, the free, sovereign individual. It looks like the digital transformation and the global network society are challenging this assumption. Before talking about privacy, we must therefore answer the answer the question, what is the human being. If the human being is not what Western individualism claims, then privacy can be understood differently. There is much work to be done in this area, as it seems that the humanistic and individualistic ideology of Western industrial society has chosen to fight its last stand against the encroaching global network society over the question of privacy.

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Tesla is a Philosophical Problem

Of course, this is not about Tesla, but about intelligent-mobile- autonomous-systems (IMAS) – also known as robots. The philosophical problem comes from the fact that the robot, in this case the automobile, says “Leave the driving to us” which was an advertising slogan for Greyhound Bus. If the robot takes over the driving, and this means the decision making, then who is responsible for accidents? This was not a problem for Greyhound since the driver and in some cases the company were held liable for their mistakes. But what about the AIs? Indeed, the question of accountability, responsibility, and liability for robots and other AIs has become a major topic in digital ethics and everybody is scrambling to establish guidelines and norms for “good,” “trustworthy,” and “accountable” AI. It is at once interesting and unsettling that the ethical norms and values that the AI moralists inevitably fall back on arise from a society and a culture that knew nothing of self-driving cars or of artificial intelligence. This was a society and culture that categorized the world into stones, plants, animals, and human beings, whereby the latter alone were considered active subjects who could and should be held responsible for what they do. All the rest were mere objects, or as the law puts it, things (res). But what about the Tesla? Is it a subject or an object, a potentially responsible social actor or a mere thing? Whenever we go looking for who did it, we automatically assume some human being is the perpetrator and if we find them, we can bring them to justice. Who do we look for when the robot “commits” a crime? How do you bring an algorithm to justice? And if we decide that the robot is to be held responsible, aren’t we letting the human creators all to easily off the hook? These were the questions that the EU Parliament recently had to deal with when they discussed giving robots a special status as “electronic personalities” with much the same rights as corporations who have a “legal personality.”

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AI Now or AI as it Could Be

The 2018 Symposium organized by the AI Now Institute (https://symposium.ainowinstitute.org/) under the title of “Ethics, Organizing, and Accountability” is interesting for a number of reasons. The AI Now Institute is an interdisciplinary research institute dedicated to exploring the social implications of artificial intelligence which was founded in 2017 by Kate Crawford (https://en.wikipedia.org/wiki/Kate_Crawford and Meredith Whittaker (https://en.wikipedia.org/wiki/Meredith_Whittaker) and is housed at the Ney York University.

The name is significant. AI “now” is indeed about AI as it is now, that is, not as it could and should be. Emphasizing the “now” has a critical edge. The focus is on what AI is actually doing, or more accurately, not doing right in the various areas of concern to the Institute, namely law enforcement, security, and social services. The AI Now Institute’s explicit concern with the “social implications” of AI translates into a rather one-sided civil rights perspective. What the institute explores are primarily the dangers of AI with regard to civil rights issues. This is well and good. It is necessary and of great use for preventing misuse or even abuse of the technology. But is it enough to claim that simply dropping AI as it is now into a social, economic, and political reality riddled with discrimination and inequality will not necessarily enhance civil rights and that the technology should therefore either not be used at all or if it is used, then under strict regulative control? Should one not be willing and able to consider the potential of AI to address civil rights issues and correct past failings, and perhaps even to start constructively dealing with the long-standing injustices the Institute is primarily concerned with? Finally, quite apart from the fact that the social implications of AI go way beyond civil rights issues, should not the positive results of AI in the areas of law enforcement, crime prevention, security, and social services also be thrown onto the scale before deciding to stop deployment of AI solutions? One cannot escape the impression that the general tenor of the participants at the symposium is the throw the baby out with the bathwater.

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Network Publicy Governance and Cyber Security

Hardly a day goes by that the media do not confront us with headlines on the latest breaches, hacks, and attacks, whether political, criminal, or both and which effect all areas of society. Many of these attacks are not even new, but sometimes years old and have only recently been discovered and reported. It is therefore reasonable to assume that there are many security breaches that we don’t know about and perhaps, for various reasons, never will. At least with regard to what we do know, the cost of cybercrime and cyber attacks has been estimated in the hundreds of billions of dollars, quite apart from the other damaging effects, for example, loss of trust in the effectiveness of our law enforcement and security institutions.  It has become apparent that traditional law enforcement and security measures do not work when it comes to preventing or combatting cyber-warfare, cyber-crime, and cyber-terrorism. For example, it is often difficult to find the scene of the crime, the weapons or tools used in the crime, to assess the damage done, or determine who is responsible. And even if it is possible to find out who did it, this information is mostly useless. One is left with the impression that despite enormous efforts by law enforcement and security institutions, cybercriminals and hackers move through our networks with impunity.

Of course, there are many reasons for this, including our own negligence. We ourselves, whether it be infrastructure and software providers or users are often a major part of the problem. The state of simple and normal “digital hygiene,” such as updates, anti-virus software, strong passwords, and so on is so deplorable that it makes you WANNACRY.

What can we do? Whereas new technologies of trust by design and new networked organizational models are slowly becoming focuses of interest for cyber security solutions, legal and ethical proposals seem not to have moved beyond positions developed in the bygone industrial era. The digital transformation seems not to have changed much in our conceptions of what security means and how freedom, autonomy, and human dignity are to be preserved in the information age. Although ethics and discussions of values and norms may appear of only incidental significance when standing on the front in the struggle against cyber-crime, cyber-warfare, and cyber-terrorism, they play a very important role in the foundational regulative frameworks that condition law enforcement and security strategies. For this reason, it is perhaps time to take a critical look at ethics with regard to cyber security.

If values and norms do not come from God or his representatives on Earth – including pure reason –, and if they are not hardwired into our DNA, then it is at least plausible that they emerge from the interactions of social actors. What has become apparent in the digital era is that technologies, artifacts, and non-humans must also be considered to be social actors. Non-humans have become our partners in constructing social order. This means that the “affordances” of information and communication technologies (ICTs), contribute to our norms and values. It is the network as a whole that is the actor and the actor is always a network. Let us therefore ask: What do networks want? What are the norms inherent in the affordances of ICTs?

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