How to make sense of the I in AI? — Director’s cut

Christian Hugo Hoffmann
12 min readApr 23, 2022

Contributions on capabilities and projected capabilities of Artificial Intelligence (AI) by researchers and other experts, many of them from non-engineers, trained outside the field of AI research or computer science abound. My book “The quest for a universal theory of intelligence: The mind, the machine, and singularity hypotheses” published with De Gruyter is one of them. Yet, at the same time misperceptions and associated fears of AI abound too and are being nurtured by the absence of refutable, rigorous and bold perspectives on what just happened in the scientific and technical development of AI, therefore, leaving much to imagination. My book is not one of them. Unlike some red herrings where the respective authors lack pertinent (book) knowledge or promote ill-guided, spurious scenarios, my work attempts to avoid that trap by adhering mainly to a strictly philosophical endeavor (a field where its author has been trained).

There is an art of which every human being should be a master, the art of reflection. Very pertinent is the question which the English poet Samuel Taylor Coleridge puts, — “If you are not a thinking man, to what purpose are you a man at all?” Daniel Kahneman differentiates between “Thinking, Fast and Slow”. Yet, both instinctive and emotional thinking (what he calls fast thinking) and more deliberative, more logical or analytical thinking (what he calls slow thinking) can be superficial and quick, as well as premature and insufficient. In our time where analytical and quick thinking is often praised, rewarded and overrated, it might really go astray or might only be indispensable because people have begun too late to think about an issue. Thus, deep thinking, which takes time, ought to be honored.

As deep thinkers, we stumble upon the conundrum of our time in the so-called second machine age: Many people in AI have not thought deeply about the key term in “AI”: “intelligence”. Max Tegmark, for example, shares an anecdote from a symposium on AI which he attended and which was organized by the Swedish Nobel Foundation: “[W]hen a panel of leading AI researchers were asked to define intelligence, they argued at length without reaching consensus. We found this quite funny: there’s no agreement on what intelligence is even among intelligent intelligence researchers!” Most researchers in AI do not even touch upon the concept — be it that they have putatively more important things to say (which not seldom leads to technical disputes or wild speculations like about singularity or superintelligence), be it that it would be beyond the parochial scope of a ten to twenty page long research article.

This photo which is used by a Swiss university (of applied science) is one of (too) many examples that show that intelligence and/or AI are not well-understood. At the biological center of human intelligence is the human brain which is far from being rivaled by any past, current or foreseeable machines. Today’s cutting-edge machines are closer to a toaster in terms of their “intelligence” than “they” are to us. Source.

Sadly, other intelligence research disciplines, including philosophy, are not doing much better in this regard. Most notably, perhaps, psychology has been dealing with the nature and role of intelligence for more than 100 years. Yet, it has been biased towards human intelligence and measurable traits like spatial or linguistic abilities.

One of the most famous studies of experts’ conceptions of human intelligence was done by the editors of the Journal of Educational Psychology (“Intelligence and its measurement”, 1921). The blatant ambiguity, variability and heterogeneity of the answers in that issue illustrate the cacophony in intelligence research. Source.

In a time where the intelligent behaviors of smart animals like crows and octopi as well as of artificial animals, from social robots to cognitive assistants, electrify, new answers for meaningful comparison with other kinds of intelligence are urgently needed. We thus wonder, how can different intelligent systems, from human to biological to artificial, be catalogued, evaluated, and contrasted, with representations and projections that offer meaningful insights?

In my book, I identify the gap that albeit much has been explored in the philosophy of AI, the general key term of intelligence remains opaque in this connection. The ambitious and ambiguous word “intelligence”, and only as a derivative artificial intelligence, is the target of philosophical explanation. The objective in my book is not to introduce a new definition as it would only stipulate a meaning of the word “intelligence” while violating how people use it in real life. By contrast, the objective is to lay the cornerstone of a universal theory of intelligence, diminishing our uncertainty about the objects we apply the concept to. It not only describes what intelligence is, but comes with true explanatory power yielding orientation and clear as well as reliable predictions and elucidating why things are the way they are: for instance, why is a toaster less intelligent than my dog? Does it make sense at all to call a toaster intelligent? Would DeepMind’s program AlphaGo outperform a professor in chess?

Deep learning programs such as AlphaGo which became in 2015 the first computer Go program to “beat” a human professional Go player and affiliated statistical methods, backed by unimagined computational power and reams of Big Data, are “accomplishing” levels of performance which trounce the achievements of the earlier phase. Source.

As a preview of what is to come in the book which is accessible HERE, the treatise is composed of four distinct parts. In Part I, we position the quest for what intelligence is in the context of discovering where it can be found, i.e., in what kinds of creatures, which results in a tour de force through human, animal, and artificial intelligence. Part II turns to the gist of the matter by seeking to understand why we ascribe intelligence to some, but not to others and what we mean by that, thereby erecting a causal theory of intelligence. Subsequently, the main work is done. Part III and IV, both significantly shorter in length, underpin the theory development contribution through testing its application. The former is dedicated to the application to present-day and past AI systems whilst the latter elaborates on hypotheses about possible Strong AI. The book is available at:

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My doctorate: A singular history-making incident at Sorbonne in more than one sense

This author who is not only passionate about AI in academia, but also as a tech entrepreneur by heart having founded three software start-ups in Germany, Switzerland, and Malawi, is highly qualified for the presented book for numerous reasons. First and foremost, the book was written against the background of my in-depth doctoral research which I completed on March 11, 2021 at the Institut d’histoire et de philosophie des sciences et des techniques (IHPST) in Paris. My PhD work was supervised at that point in time by Prof. Max Kistler (Paris 1 Panthéon-Sorbonne / IHPST) and Prof. Michael Esfeld (Université de Lausanne). Following good academic practice, both thesis directors were well-familiar with my doctoral project in the sense that different meetings, phone calls took place and different versions of the text were read and commented on. I responded to all comments comprehensively which was shared with the supervisors and led after a few iterations to a final version of the manuscript which was submitted in the first half of March 2021. Paired with the fact that I only officially started my PhD in fall 2020, and factually in September 2020, my doctorate wrote history at Paris 1. Nobody before ever submitted a PhD thesis in Philosophy after such a short time, a point which I actually alluded to in the manuscript itself.

The main building of the Université Paris 1 Panthéon-Sorbonne in the Quartier Latin in Paris, one of the many universities that emanated from the former and famous Sorbonne. The IHPST is one of the research institutes associated with the Paris 1. Source.

But the singularity of the process doesn’t end here. Three more occurrences in connection with my PhD are extraordinary. The first is that on April 16, 2021, a formal meeting of 1st and 2nd year PhD students from IHPST took place where those newcomers, including myself, were asked to present their ambitions and PhD proposal to their peers as well as the faculty at IHPST. At that point in time, my work was already submitted. Nonetheless, Max (back then my director at IHPST) asked me to pretend that the findings I shared are only work in progress or ideas for future research. In other words, I was asked to lie to the other participants. The reason which was given me was that it would already be enough for them to digest that I do my PhD thesis in English which is probably everywhere outside of France or Philosophy in France common since the lingua franca in academia is English and not French. And in fact, I was the only presenter who presented in English.

The next outstanding fact is that, surprisingly, my PhD thesis was rejected by external reviewers who were not involved in my PhD project, but were asked to write the so-called pré-rapports. What is peculiar about this outcome is on the one hand that something like this has never happened: A soutenance / defense was already scheduled for June 29, 2021, a jury was invited, but with the vote from the pré-rapports it was canceled. On the other, the cancelation puts the thesis directors in the limelight. Thesis directors only recommend the submission of doctoral theses by their students if they are convinced that the respective doctoral work passes the examination in the pré-rapports. In my case and apparently for the first time (according to Max), they failed.

This incident was extremely embarrassing to the institution. My supervisor Max who coordinated himself with the Head of the Ecole Doctorale at Paris 1, Denis Forest, then proposed as a solution to sweep the broken pieces of my manuscript under the carpet. The idea was to abandon my path-breaking research project which only a few months earlier had been approved by both former theses directors and to act like I just changed my mind about pursuing my research which in contrast to what actually happened in my case is not uncommon in the first year of a PhD program and would fit well my background and profile: Why does Christian want to do a second PhD after graduating with a PhD in Finance with distinction, after having worked as both an Assistant Professor of Finance and an accomplished entrepreneur? How can somebody like this be serious about a second PhD? In Philosophy? Ergo, the perfect cover story to sell by Paris 1. Not quite, at least not if you look closer.

Broader lessons for philosophy and academia

On a personal note, I was allowed to continue my PhD studies at the Karlsruhe Institute of Technology (KIT) which, however, turned out to be the most bureaucratic jungle an efficiency-seeking and effectiveness-appreciating individual and entrepreneur could think of — but that’s the subject of another story. KIT’s Institute for Technology Assessment and Systems Analysis (ITAS), the “leading institute for technology assessment in Germany and worldwide”, welcomed and hosted me as of July 2021 due to the interdisciplinarity in its DNA, its focus on not only AI, but also on impact outside of scientific communities, and an openness to apply systems thinking. I submitted my doctoral thesis at the KIT in September 2021 whereupon I received the positive reviews by the two supervisors of my doctoral work, Prof. Dr. Armin Grunwald and Prof. Dr. Alfred Nordmann, at the beginning of March 2022. The reason why I could submit my thesis at the ITAS in September 2021, a thesis which I wrote the 5 to 6 months prior to March 11, 2021, i.e., before I joined the ITAS at all, is twofold: On the one hand, my work came together in solitude in an armchair in Switzerland and not as part of a research team in Paris. I mainly worked on my book independently (not fully independently of course because we talk about our ideas with others and read books or papers by others, which then influences our thinking and its output — or more metaphorically speaking, we stand on the shoulders of giants) and, overall, I experienced more resistance than support from the faculty at Paris 1. On the other hand, I was not officially disqualified from the PhD program at IHPST since my endeavor had been thwarted by the pré-reviewers as spelled out above. Despite that good news from the ITAS, it is probably more interesting to the versed reader to hear about my take on the ramifications of the events (s)he read about above in the bigger picture. Therefore, I wish to touch upon some broader lessons for philosophy and academia from the Parisian odyssey in the following.

Perhaps less prestigious than the Sorbonne among the broader public, but evidentially (given my case) also less antiquated?. The main building of the ITAS at the Karlsruhe Institute of Technology (KIT) in Karlsruhe, Germany. Source.
The final sections of the review of eight pages by my main doctoral supervisor Prof. Dr. Armin Grunwald, KIT.

Let’s recall first that I have shown my competency to talk about AI (philosophy and economics of AI). This achievement is demonstrated by a multitude of AI-related publications in peer-reviewed scientific journals, newspapers and blogs; by my former position as Deputy Director and Head of AI at the Swiss Fintech Innovation Lab at the University of Zurich; and, not least, by the fact that I founded three software startups (out of which I exited one successfully, another one was shut down, and the third is still running) and worked in a leading function at a robotics firm in Zurich, currently valued with more than CHF 100M.

Moreover, I possess a special profile / background for writing about AI and intelligence. I studied philosophy and economics at leading universities throughout the world (LSE and Yale University among others). I completed a Postdoc on Fintech at ETH Zurich. This unusual perspective of a philosopher/economist/entrepreneur on AI generates novel and stimulating insights. And now we are getting to the crux of the matter.

The two pré-reviewers that handed in the pré-rapports had not declined my work because they thought it would be of poor quality. Quite the opposite, here are some quotes: “The dissertation submitted by Christian Hoffmann is a very competent and beautiful popular nonfiction book”. “The book is enormously erudite, as the huge bibliography displays. At all occasions the text can and does present appropriate quotes from many centuries and faculties. This is impressive.” Or: “Its style is brisk and lively (and flawless, as far as I can tell). It is well organized, with break-out sessions, summaries (take-aways), many explanatory graphics, etc. In this way it is easy to follow and quite pleasant reading”. Interestingly, the book itself claims the same thing, namely that it is open to a broader audience, to all those who are interested in learning about intelligence and intelligence in AI, and not just to philosophers in the ivory tower. However, both pré-reviewers also claim that despite its virtues my text cannot be a philosophical piece of work at the same time. Why? Here the argumentation breaks down. One pré-reviewer, Prof. Michael Hampe from ETH Zurich, bluntly stipulates that there is no philosophical problem to start with (which has to be inconsistent with what at least another expert, my former thesis director Prof. Max Kistler, thinks or thought since he proposed the topic about investigating the concept of intelligence in our age of so-called machine intelligence in the first place). The other pré-reviewer missed the accurateness and rigorousness in my text that characterize academic philosophical work. Or is it maybe just the fact that my manuscript misses the avalanche of footnotes that mark the 200-year-old tradition of “great” philosophical thinking, but that render them unreadable to most at the end of the day?

Impressions from my “Dissertation Vacation”: This is one of the important places where I was writing my book, a beautiful chalet in Les Diablerets in Vaud, Switzerland: Working/writing in the morning, skiing, sauna in the afternoon.

The elephant in the room question is if perhaps my work was rejected by the professorial gatekeepers of academic philosophy simply because it is accessible to too many. What this discussion with the pré-reviewers and distinguished professors of philosophy would eventually come down to is the issue what is philosophy, a philosophical problem or question? And interestingly, my work, even though it’s primarily about intelligence and AI, addresses this point and provides, how I find, a not less interesting answer. On the one hand, I put myself on the shoulders of giants (like Wittgenstein or Carnap) by acknowledging that philosophy, following the so-called conceptual turn, deals with investigating and analyzing concepts that require clarification. Not every concept, problem or question is of philosophical interest, but as I argue in my book and in consonance with Prof. Max Kistler and Prof. Michael Esfeld, but for whatever reason unlike Prof. Hampe, the concept of intelligence is such a philosophically interesting concept. On the other hand, however, I break with some parts of the great philosophical tradition of analytic thinking. This is neither a flaw the reviewers unveiled, nor an accident. I did it on purpose and for good reasons as I argue in my book.

For example, in the introduction to Part II, I write: “For better or for worse, analytic philosophy has largely proceeded according to a parallel method, an approach of analyses or explications and counterexamples. Analytic philosophy has walked the path of negation. […] In this Part II, Scaffolding intelligence, we depart from this tradition of analyses and counterexamples in favor of more constructivism and a higher conceptual variety.” The point I wish to make in this and other passages is that some concepts, including the central concept of intelligence, are complex systems, family concepts that cannot be reduced to necessary conditions which together are sufficient for explicating the concept in question. Rather, something more than analysis is needed and found in systems thinking which encompasses not just analysis, but also synthesis! That the guild of analytic philosophy has a problem with questioning the value of analysis can be obvious, but why does academic philosophy in general refrain from becoming affected (or improved?) by new ways of thinking and working? Or rather by innovation as I, as an entrepreneur, would phrase it.



Christian Hugo Hoffmann

👉 🚀📧 Serial entrepreneur/cluster-preneur, libertarian, as well as a researcher on AI, complexity, and risk management