Mission AI

Front matter

Research for Policy

J Haroon Sheikh Ep ` Corien Prins „ik | Erik Schrijvers U en

Mission Al

Preface

This book is a translation and adaptation of the Dutch report Opgave Al. De Nieuwe Systeemtechnologie, which was presented to the Minister of Economic Affairs and Climate Policy in 2021.' In this study, the Netherlands Scientific Council for Government Policy (WRR) characterizes artificial intelligence as a ‘system technology’ that fundamentally alters society and establishes five overarching tasks for governments to embed Al into society.

This publication was written by Prof. Corien Prins (Chair and primary Council Member, LLM), Prof. Dr. Haroon Sheikh (Senior Research Fellow), and Dr. Erik Schrijvers (Senior Research Fellow), with the support of Drs. Eline de Jong (exstaff member), Tessel van Oirsouw (intern, BA BSc), Prof. Dr. Mark Bovens (Council Member, LLM) and Monique Steijns (staff member, LLM).

Mission Al. The New System Technology is the product of the extensive study of academic literature, policy documents and analysis.

In addition, we have conducted interviews with over 170 external experts in the public and private sectors, both from the Netherlands and abroad. The interviews include conversations with municipalities, regulators, High Councils of State, scientists, company representatives, actors from civil society organizations and members of the Dutch AI Coalition. We are grateful for their contribution to this report. Their names are listed at the end of this report. During the final phase of the project, texts were reviewed by Prof. Dr. Luc Steels (Emeritus Professor of Artificial Intelligence, Vrije Universiteit Brussel), Marleen Stikker and Tom Demeyer (Director and CTO of Waag, respectively), Prof. Dr. Stavros Zouridis (Council Member of the Dutch Safety Board, LLM), Prof. Dr. José van Dijck (Professor of Media Studies, Utrecht University) and Prof. Dr. Koen Frenken (Professor of Innovation Studies, Utrecht University). We thank them for their comments and valuable suggestions.

Den Haag, The Netherlands Haroon Sheikh Corien Prins Erik Schrijvers

'The original Dutch publication (2021) has been adapted for an international audience but has not been updated.

xi

Contents

I Tntroductión o en reve ater eden Rt 1 Li -Alata TERS Pent cowed ote b cate ben dbadeeeseiseads 1 1.2 AI Leaves the Lab and Enters Society... 3 13 Technology and Public VAES. sans soera see omire ri 5 IA A Mistorcal Perspective ‚as 00505 reerd derma wes F 1 The Five TASKE..rrcesnrernerverdverddanen ne bek 9 Le - ieee OF The Ropi eessen rene al 11 Ke a 22 E A E EE T REE ER OS 12

Part I Building Blocks: Introducing and Interpreting AI

as a New System Technology, Similar to Electricity and the Internal Combustion Engine

aL. Benne arrsnarsrtdrekerhatedatkadindedikies 15 22; el PAGE Une LAB rise bi diieed eee at eee! 20 2S SMS LAB rresia tipae ew Ee d eee ema ehane 28 e e e ceo 2acd TE EATE TEE E A tnd dee

31 “Momentum from Lab to Society oe ends wow 43 3.2 The Practical Application of AL. rsr sereen verveners 49 33 Alasa Phenomenon in Society. cess ssarvarernrsrvdn dere 59 34 The Future of the Lab 23.00 cscnocceeeics seueeestewes reit 7 EN 79

4 Alasa System Technology... aoe 85 4) Classification of Technologies. ...:...cs00.skecs0eenseaees 86 xiv Contents

4.5 Overarching Task 3: Engagement .… ne. 4.6 Overarching Task 4: Regulation nen. 4,7 Overarching Task 5: Positioning .…… eenen.

Part III Agenda: Conclusions and Recommendations for AI Policy in the Netherlands

10 Policy for AI as a System Technology aa.

Contents Xv 10.6 Transition 5: From Nation to Network... 363

About the Authors

Haroon Sheikh is a senior scientist and project coordinator at the Dutch Scientific Council for Government Policy and a Professor in The Strategic Governance of Global Technologies at VU University. His research focuses on the intersection of new technology and international relations. Haroon studied philosophy, political science and public administration at Leiden and Oxford University and did his PhD in philosophy on the relationship between tradition and modernity at VU University. He worked over a decade in the financial sector and headed Freedomlab Thinktank in Amsterdam. Haroon has written several books in the field of geopolitics.

Corien Prins Regulatory challenges and questions around the introduction of digital technologies have been on Corien Prins’ agenda for three decades. In 1995, she founded what is now the Tilburg Institute for Law, Technology, and Society—a world-renowned research center on law, society and technology. In her research on the impact of emerging technologies on individuals and society, she has focused on the role of regulation, law, fundamental values and human rights. In 2017, Prins was appointed chair of the Netherlands Scientific Council for Government Policy (WRR), which advises the Dutch government and parliament on strategic issues likely to have significant political and societal consequences. Prins has an abiding interest in the interdependency of the digital and physical worlds. One of her current research foci within the broader theme of artificial intelligence is its use by the judiciary. Here she seeks to understand the implications of using AI for the core values of the judiciary—impartiality, independence and due process. Other research topics of Prins relate to the development of legal measures to gain a clearer picture of which parties, digital processes and services are key to the functioning of critical (vital) processes in society. She thereby looks at the chains and networks that support key processes and investigates whether digitalization necessitates changes to the prioritization of assets that are essential for the functioning of a society and economy. Her other research interests include the implications of digital technologies for democracy in a globalized world, the use of digital technologies and personal autonomy, and privacy and personal data protection.

xvii xviii About the Authors

Erik Schrijvers is senior scientist and project coordinator at the Dutch Scientific Council for Government Policy. He is also a member of the Supervisory Board of DEN, knowledge institute for culture and digital transformation. His research focuses on the intersection of digital technology, culture and policy. He studied history of international relations and philosophy at Utrecht University and obtained his PhD with a thesis on the history of forms of extra-parliamentary representation in the Netherlands. In 2016 and 2017, he worked for the Ministry of the Interior and Kingdom Relations, where he was responsible for the research and reporting of the study group Information Society and Government.

Abbreviations

AGI Artificial General Intelligence

AI HLEG High-Level Expert Group on AI

AIV Advisory Council on International Affairs ALLAI Alliance for Artificial Intelligence Netherlands ANNs Artificial Neural Networks

GDPR General Data Protection Regulation

CAPTCHA Completely Automated Public Turing-tests to tell Computers and Humans Apart

CCW Convention on Certain Conventional Weapons

CEN Comité Européen de Normalisation

CENELEC Comité Européen de Normalisation Electrotechnique

CPU Central Processing Unit

DARPA Defense Advanced Research Projects Agency

DIU Defense Innovation Unit

DL Deep Learning

DMA Digital Markets Act

DSA Digital Services Act

GOFAI Good Old-Fashioned AI

GPT General Purpose Technology

GPU Graphic Processing Unit

HRM Human Resources Management

ICAI Innovation Center for Artificial Intelligence

IEC International Electrotechnical Commission

IEEE Institute of Electrical and Electronics Engineers

ISO International Organization for Standardization

ITU International Telecommunication Union

JAIC Joint Artificial Intelligence Center

XX

ML MVP NEN NSCAI OECD OSS SAPAI TPU UN

Abbreviations

Machine Learning

Minimal Viable Product

Royal Netherlands Standardization Institute

National Security Commission on Artificial Intelligence Organisation for Economic Co-operation and Development Open-Source Software

Strategic Action Plan for Al

Tensor Processing Unit

United Nations

Chapter 1 A) Introduction Geek for 1.1 AI at a Turning Point

A robot wrote this entire article. Are you scared yet, human? I’m not a human. I’m a robot. A thinking robot. I use only 0.12% of my cognitive capacity.

This report, published by the Scientific Council for Government Policy (WRR), has been written entirely by humans. Likewise, we expect that advisory reports like this one will continue to be written by humans. The same applies to the larger part of journalism, despite what the introductory quote might suggest. In fact, it later became apparent that humans had indeed written much of the article that opened with these words, which appeared in The Guardian on 8 September 2020. Nevertheless, the stir caused by the article made one thing clear: artificial intelligence (AI) is now front-page news.

The term artificial intelligence was first coined in the 1950s. Since then, scientists have been working to develop systems capable of performing tasks that require cognitive skills and operating with some degree of autonomy. In recent years, however, something has changed. Whereas AI used to be the domain of scientists, enthusiasts and science-fiction lovers, the technology now speaks to the imagination of a wider audience. In other words, AI appears to have taken off, with irrevocable effects for society. Here is a small selection of news stories from the past few years.

Google’s AlphaGo program beats defending champion Lee Sedol at the board game Go. When IBM’s Deep Blue beat chess champion Garry Kasparov in the 1990s, the expectation was that it would take a century before a computer could also win against a human at the more complex game of Go.

Microsoft brings out Tay, an Al bot that learns from human behaviour on social media. Within a few hours Tay becomes a malevolent troll, making hateful comments about women and posting fascist tweets.

© The Author(s) 2023 1 H. Sheikh et al., Mission AI, Research for Policy, https://doi.org/10.1007/978-3-03 1-21448-6_1

Stories spread that Facebook’s AI programs have developed their own language, which people cannot understand. These stories appeal directly to visions of uncontrollable Al and so the programs are quickly shut down.

Sophia, a robot created by Hanson Robotics, speaks at a conference in Saudi Arabia and is granted citizenship.

CEO Sundar Pichai demonstrates Google Duplex, an Al assistant whose voice is claimed to be indistinguishable from that of a human and can perform tasks such as making dinner reservations.

A deep-fake video of President Barack Obama appears in which he seems to be giving a speech that is actually being read by comedian Jordan Peele.

IBM’s Project Debater takes on one of the world’s best debaters, Harish Natarajan, about subsidizing nursery schools. Following an argumentative showdown between man and machine, the judges pronounce Natarajan the winner.

The Guardian publishes an essay written by GPT-3, a language generator developed by OpenAL, in which it argues that humans need not feel threatened by AI.

Boston Dynamics publishes a video of its robots dancing to The Contours’ Do You Love Me?

Big business is pouring money in AI, and those investments are clearly yielding results. The technology is becoming embedded in people’s daily lives through Google searches, Facebook feeds, use of Apple’s digital assistant Siri and recommendations from Amazon and Netflix. Many European companies, from Siemens and ASML to Airbus and Spotify, are using AI to personalize services, update products and optimize business processes. AI’s momentum is also apparent outside the business community.

Governments, too, are taking an interest. In recent years, numerous countries have published national AI strategies. In the Netherlands, for example, State Secretary Mona Keijzer presented the Strategic Action Plan for AI (SAPAT) in October 2019. Furthermore, many governments have become major AI users. Police forces, militaries and customs services use the technology for security purposes, for example, while hospitals deploy it to support care processes, infrastructure ministries to improve public space and local governments for smart city projects.

Popular culture has embraced AI as well. Particularly as a source for dystopian portrayals of the future. Movies featuring malevolent computer systems are a longstanding staple of the film industry. Notable examples include Colossus: The Forbin Project (1968) and The Terminator (1984). In recent years, interest in a future populated by increasingly intelligent computers has been revived in movies and series such as The Matrix, I Robot, Her, Ex Machina, Artificial Intelligence, Transcendence, Next, Black Mirror and Westworld.

Besides these fictional depictions of a dystopian future, contemporary controversies surrounding the use of AI have emerged as a prominent topic of public debate. Various social movements have been addressing both the risks and actual

1.2 Al Leaves the Lab and Enters Society 3 malpractices. In the military branch, for example, there is an ongoing debate about drones that can automatically identify and eliminate targets, also known as ‘lethal autonomous weapons systems’ or — more disturbingly — ‘killer robots’. In 2015 a large group of scientists wrote an open letter to the United Nations calling for such weapons to be banned. A second letter followed in 2017, this time also signed by the founders of many companies active in the field.

The self-driving car is another example of an application that has provoked widespread debate. In 2016 Joshua D. Brown became the first person to be killed in a self-driving car. Since then, there have been numerous fatalities involving Uber and Tesla vehicles. Another contentious application is facial recognition, which uses computer vision to identify faces in moving or still images. The fear of totalitarian surveillance has prompted calls for facial recognition to be banned. That led several US cities, including San Francisco, Boston and Portland, to regulate or prohibit the technology. On this side of the Atlantic, the European Commission has drafted an Artificial Intelligence Act incorporating strict restrictions on the use of facial recognition. In the Netherlands, recent Al-related controversies include the judicial prohibition of System Risk Indication (SyRI, a technology intended to trace fraud) and the so-called ‘Dutch childcare benefits scandal’ (Toeslagenaffaire), caused by the Dutch Tax Administration’s use of algorithms to detect supposedly fraudulent claims for childcare benefits. That led to thousands of parents being wrongly accused and eventually brought down the third Rutte government.

1.2 AI Leaves the Lab and Enters Society

In short, AI is at a turning point. The technology is becoming part of our everyday lives, kicking up dust along the way. We can sum up this transition as AI leaving the laboratory and entering society (see Fig. 1.1). Although, of course, that is a simplified representation of reality. In today’s world, no hard and fast line can be drawn

Al in the lab Al in society

Fig. 1.1 Alis leaving the lab and entering society between the laboratory, the research space and the public domain. Laboratories are part of society, and ideas, people and practices are continually moving back and forth between the two. Moreover, the laboratory is not a fixed entity. The facility Louis Pasteur worked in cannot be compared with a Cold War computer lab or a modern-day global research institute. Nevertheless, the transition from lab to society is a useful way of referring to the current movement in the field of AI.

The origin of artificial intelligence as a scientific concept can be traced back to a research programme at Dartmouth College, New Hampshire, USA, in 1956. People had of course been fantasizing about AI long before then, but that programme marked the start of systematic laboratory research into the subject. In the decades that followed, various forms of AI found their way from that lab into society. Programs to play checkers and chess have been around since the 1960s, and decision trees have long been an established feature of many digital systems. Since the 1980s we have seen the rise of ‘expert systems’: programs that, say, incorporate medical knowledge to support doctors’ decision-making. From the start, the discipline has yielded startling experiments and demonstrations that spoke to the imagination of the general public. Yet AI’s practical impact on the economy and society remained relatively minor. Until recently.

It is only in the past decade that AI’s transition from lab to society has really gathered momentum. It is now beginning to play a socially significant role, with its development being shaped not only by the research community but also by actors with their own particular interests, especially in the world of business. That was exemplified by Google’s acquisition of the British research lab DeepMind in 2014. DeepMind was responsible for the AlphaGo program mentioned above, which defeated the defending Go champion in 2016. Big technology companies see AI as an important driver of profit. Indeed, Google and Microsoft now describe themselves as ‘Al-first businesses’. Alongside these dominant technology platforms, a growing number of innovative start-ups and established businesses in other sectors are increasingly focusing on AI as well.

The number of national AI strategies shows that governments are equally interested in this technology. They see it not only as an important driver of future economic growth and a tool for improving public services, but also as a potential source of risk requiring regulation and supervision. Actors in civil society are becoming increasingly engaged, too, as they seek to defend the vulnerable, campaign for normative frameworks or test the legality of certain practices in the courts. In recent years the research community has both contributed technical expertise and entered the normative debate regarding the applications of AI.

Finally, the general public is now taking an interest in AI. Not only as a result of the intensifying discourse about various visions of the future, but also because the technology’s impact is becoming more and more tangible. Algorithms are increasingly playing a role in services people depend on, such as education, health and

'See, for example, Latour, 1983.

1.3 Technology and Public Values 5 benefit payments. Furthermore, AI is changing the nature of many professions, requiring people to acquire new skills.

No one knows how AI will develop in the future. To a significant extent, how AI influences society will depend on how the aforementioned actors view and deal with it. They all have their own interests and values, and their own means of defending and advancing their interests. Sometimes these coincide, as when pressure groups and the media work together to support citizens who have been scammed, or when governments and companies collaborate to reinforce a nation’s earning potential. But clashes also occur. For example, there is tension between academics emphasizing openness in research and businesses protecting commercially sensitive information. Private citizens and governments can also find themselves at odds over the use of surveillance technology, where security and privacy are difficult to reconcile.

Ensuring that the use of AI is consistent with society’s core values requires cooperation, negotiation, familiarization, debate and conflict. In other words, making it part of our lives will entail a complex process of social integration. What is the best way to guide that process and to influence it where appropriate? To answer that question, two topics require further investigation: the technological nature of AI and its relationship with society.

1.3 Technology and Public Values

In this report we discuss what AI is and how the technology can be characterised. There is a vast amount of literature on the impact that AI applications have in various domains. However, to get to a cross-sectional study of the impact of AI, we need to take a step back and ask what kind of technology we are dealing with.

One of AI’s distinctive characteristics is the breadth of its applications. The academic literature refers to technologies that lend themselves to wide-ranging applications as ‘general purpose technologies’. When understood as such, AI is comparable with the steam engine, electricity and the internal combustion engine. With that in mind, this report uses analogies with earlier technologies as the basis of its reasoning. The term we have adopted to convey the nature of AI is “system technology’, with the word ‘system’ here referring to the many different technologies that comprise and are associated with AI, as well as its systemic impact on society.

Characterizing AI as a system technology has immediate implications for the way in which we consider its impact. Its influence is now the subject of a large body of literature,” as well as countless principles and charters. A recent inventory lists more than 300 sets of ethical codes and guidelines covering AI.* Prominent examples include those produced by the European Commission’s High-Level Expert Group on AI (AI HLEG), UNESCO and the AI Now Institute. Many publications

? See, for example, Vetzo et al., 2018; Kulk & van Deursen, 2020. 3Russell, 2019: 249.

link the technology’s impact to values such as explainability, transparency, non-discrimination, privacy, autonomy and liability. Establishing such connections is important and we therefore give them thorough consideration later in this report. At the same time, it is dangerous to seek to reduce Al's impact to a list of public values,* since that is inconsistent with its dynamic entry into our society.

If Al is a system technology, as we argue in this report, then its impact on public values cannot simply be reduced to a list of effects. There are several reasons for that. First, as a system technology Al is increasingly going to be used throughout society. Moreover, since we are still in the early stages of its development, no list could be anything other than provisional. On top of that, the technology is set to impact not only the ‘Al-specific’ values mentioned above but also those central to the context in which the technology itself is applied. If AI can be used in a given context, it has the potential to influence all public values relevant to that context.

The history of system technologies teaches us that AI’s effect on society is going to be both unpredictable and wide-ranging. Trains and cars influence not only mobility but also city planning, by greatly reducing the need to live close to one’s place of work. Similarly, electrical domestic appliances have changed women’s position in society. Furthermore, expectations regarding the impact of technology can prove to be incorrect. Cars, for instance, were expected to make cities cleaner by eliminating horse manure and the associated burden of disease from the urban environment.

Another significant factor is that system technologies themselves help to shape values. The car enabled long-distance travel and new forms of youth culture, thus influencing values such as privacy, freedom and autonomy. How AI will impact public values is therefore far from clear. The analyses now being undertaken are very important because they shed light on what is currently happening and are informing the debate as presently being conducted. The danger, however, is that if such analyses are interpreted as comprehensive, that might give rise to the misapprehension that the impact of AI can be managed just as long as the associated values are safeguarded.

Finally, it is important to recognize that the concept of ‘impact’ is itself misleading. If we view society and its core values as static, we are apt to regard AI as an external phenomenon with the potential to undermine those values — and the debate regarding Al is indeed often framed in such terms. However, from that perspective we are liable to lose sight of AI’s potential to change society for the better; for example, by promoting certain values more effectively. We should therefore adopt an approach that acknowledges the dynamic nature of AI’s social integration, characterizing its impact not in terms of external pressure but as a two-way interaction between technology and society.

“See also the WRR Working Paper by Ernst Hirsch Ballin regarding human rights as benchmarks for artificial intelligence (Hirsch Ballin, 2021). Rather than reviewing Al-based practices in terms of their compliance with human rights, this demonstrates how AI can help uphold and foster them. > Gordon, 2016.

1.5 Overarching Tasks for the Societal Integration of Al 7 1.4 A Historical Perspective

Any examination of AI’s social integration thus needs to bear in mind the breadth and unpredictability of the phenomenon, the interaction between society and technology and both the threats to and opportunities for reinforcing core values. How can such a complex investigation be undertaken in a way that supports government policy-making?

To guide our investigation, we have considered how societies have previously handled the large-scale adoption of new technologies and we have sought to identify historical patterns. In doing so, we have not assumed that history will repeat itself or that technology is deterministic. Indeed, this report highlights the differences between AI and previous system technologies. Nevertheless, we believe that interesting historical patterns may be discerned, which can help us to understand present-day issues. Adopting a long-term perspective sheds light on the dynamic nature of the social integration of system technologies.

Based on our study of system technologies, this report identifies five overarching tasks for embedding Al in society. These are broadly defined, in terms of the fundamental characteristics that shape a society— particularly one weaving AI into its fabric. By seeking to avoid too narrow a focus on specific topical issues, to the detriment of structural effects and changes, this approach addresses AI’s more intrinsic impact on society. Each task highlights a multitude of key values relevant to that impact or put on the line by it.

1.5 Overarching Tasks for the Societal Integration of AI

The five tasks are:

Demystification Contextualization Engagement Regulation Positioning noe

We briefly consider each of these individually. To properly understand the process of embedding Al in society, however, an insight into their interrelationships is also essential. The five tasks operate at five distinct levels and address five core questions. Demystification refers to understanding Al as technology and asks: what are we talking about? Contextualization is about applying an AI system in a particular context: How will it work? Engagement relates to the social setting of an AI system: Who should be involved? Regulation acts at the level of society as a whole, focusing on the question what rules are required? Finally, positioning is an international task: How do we relate to other countries? This breakdown is visualized in Fig. 1.2.

Fig. 1.2 Five tasks for the embedding Al in society s © p Je 2 £, 6 a

Demystification Contextualization

Societal

& En

Positioning Engagement

U

The five tasks are universal in nature. They were relevant to previous system technologies, such as electricity and the internal combustion engine, and are equally so to the societal integration of Al. Moreover, they relate to fundamental aspects of a society, such as its public sphere (demystification), business operations (contextualization), interaction between social actors (engagement), power structures (regulation) and international relations (positioning).

Although the tasks themselves are universal, the way they are actualized depends on the type of society undertaking them. For example, every society needs to work on demystification. However, the nature and organization of the Dutch public sphere and the actors active in it differ from the situation in the USA. Consequently, demystification may involve different actors in the two countries. A similar situation occurs regarding engagement. In every country it is necessary for various population groups to engage with new technology. However, the role civil society plays will differ between, say, a democratic country such as Germany and a non-democratic one such as China. The task of positioning relates to issues such as security, which are vital to society but are expressed differently in every country.

Together, the five tasks constitute the process of integrating AI within society. In that context they serve as vehicles for considering matters of vital social importance like open debate, stakeholder representation, government regulation, national security and national prosperity. Although this report examines them individually, it is important to emphasize that, in practice, they are often closely related. So, they should not be considered as self-contained or sequential, but as interconnected elements of a larger whole.

By adopting a societal task-based approach, the WRR aspires to advance the public debate regarding AI. When it began nearly 10 years ago, that was characterized by grand expectations of the future. Visionary authors predicted a world of

1.6 The Five Tasks 9 self-driving cars, free from the threat of disease, where algorithms relieved people of many onerous tasks. Others, however, warned of a dystopian future in which humans were subservient to machines.

In recent years the nature and tone of the debate have changed. AI applications have now been widely implemented, shifting the focus from future scenarios to acute topical issues. For example, it became clear that HRM algorithms were disadvantaging women while the algorithms used by security services discriminated against people of colour. Government organizations all over the world appeared to be relying on algorithms they were barely able to understand or justify. As a result, the tone of the debate has become largely negative. That should not come as a surprise. As indicated earlier, although AI is now entering society, the process of its integration is only just beginning. The current situation can be compared with the time when cars were first appearing on our streets — before seatbelts, airbags, insurance, number plates, traffic regulations or driving tests — or the early days of massproduced food and medicine, when there were no safety standards, patient information leaflets, product approval schemes or regulators. In other words, we are currently in a phase where a lot is bound to go wrong and malpractices are sure to occur, mostly due to a lack of experience or clear rules. Despite these clear risks, though, there is a danger that all the negative media coverage will cause us to lose sight of AI’s potential to make a positive contribution to society. It may also cause us to become so preoccupied with the short-term risks that we fail to recognize or address the greater threats we face.

It is therefore important to move the AI debate forward and to assess the technology’s impact on a structural basis. That implies that we should not only concern ourselves with acute issues and problems but also with developing a balanced vision of AI’s long-term integration into society. The five tasks identified above are pivotal in that regard. So, what exactly do they involve?

1.6 The Five Tasks

The first task is demystifying AI. Central to that challenge is the general public. AI has many myths attached to it, which not only distort perceptions of the technology but also sustain unrealistic expectations and disproportionate fears. For example, despite the impression given by certain companies and visionaries, the wait for self-driving cars has dragged on for years. The unrealistic nature of the predictions soon becomes apparent once one truly understands the huge challenges facing AI in this field. Concerns that malevolent AI might take over the world are equally unrealistic. Hence, demystification depends on an informed perception of what AI is and is not capable of, now and in the future. In short, what are we talking about here? We will see that myths exist about the way AI works, about its likely future impact and about digital technologies in general.