For a long time, this reviewer has been looking for a good book aimed at busy business executives who wish to get a broad view of the many impacts of modern IT on leaders, businesses and our society at large. Tse, Esposito and Goh’s The AI Republic: Building the Nexus Between Humans and Intelligent Automation is this long-awaited book!
The authors provide a relatively broad, almost all-inclusive definition of artificial intelligence (AI), labeling many issues as AI that would more naturally be considered part of broader IT. (This reviewer’s understanding of AI is narrower: an algorithm or a statistical model that has prediction power through pattern-identification and inferences from available training data.) However we define the term AI, the authors identify three essential major developmental stages of this new technology:
The power of the human dimension: People should be in charge, not machines.
The social effects: No net job loss should be expected, as the new technology tends to create more jobs than those being lost.
The education requirement: Future generations will need education and training that take AI development into account to best engage with this technology.
The three authors are deeply involved in these matters. All three are the co-founders of Nexus Frontier Tech, a UK-based software development company. Dr. Tse is a professor at the ESCP European Business School. Dr. Esposito is also a professor at the Hult International Business School and Harvard University as well as an expert panelist and a regular contributor at the Lorange Network. Mr. Goh is the CEO of Nexus Frontier Tech. Thus, this trio undoubtedly represents an unusual body of relevant competences.
Two main messages underpin the entire book:
AI will take over many of today’s basic human tasks, and it will alter many ways in which humans do things.
High costs, lack of time and some large companies’ monopolistic policies in directing AI usage hold progress back.
The authors kick off the book with a definition of AI. As mentioned earlier, the definition is very broad, in this reviewer’s opinion! The authors then discuss the concepts of artificial narrow intelligence and its counterpart, artificial general intelligence, and how the former in particular will free humans from many mundane tasks. Counterintuitively to some, this increased reliance on machines will make human skills more important, not less. “As society becomes increasingly reliant on AI, human expertise, problem-solving, behavioral judgements and creativity will be ever more important in society.
This fourth Industrial Revolution we are currently undergoing relies on technology’s ability to converge toward dramatically better value creation approaches. One example of such convergence is Uber’s underlying matching algorithm. Thus the company’s value creation relies on:
The supply and demand for a transportation service are being matched, thus providing a valuable service to consumers.
The service is cheaper than conventional competition.
Less pollution is generated thanks to the vehicle’s increased occupancy.
Many new drivers now generate an income.
Not only are machines faster than humans in some high-order reasoning functions, but in fact, it would simply be impossible for humans to take over from Uber’s algorithm!
The authors foresee three main business motivations for AI:
Error reduction
Efficiency improvement
New business opportunities development
These motivations are supported by three key abilities that good AI should encompass:
Recognition
Prediction
Prescription
According to the authors, the actual uses of AI are de facto not as extensive as were a priori expected. They claim that the major industrial players – FAANG (Facebook, Apple, Amazon, Netflix, Google) in the US and BAT (Baidu, Alibaba, Tencent) in China – tend to acquire many emerging AI startups, making it too expensive and difficult for other competitors to make full use of this technology’s novel capabilities. These actions predominantly hurt smaller firms and result in expertise shortage. To attend to these issues, at least in part, the authors co-founded Nexus Frontier Tech, which offers its podder.ai software primarily to smaller companies. Based on their market experience applying AI in various business contexts, Tse, Esposito and Goh share several practical recommendations:
Be specific and concrete regarding the tasks to be covered through the programming efforts that are ahead. This focus will decrease the probability of errors.
Be realistic regarding the risks involved, and in particular, have realistic expectations regarding the capabilities of the people involved in a given project.
Get the “last mile” right—ensure projects’ full completion and avoid “almost there” mentalities.
Be realistic about the data required—less data, but of high quality, may suffice!
The government’s role is crucial in supporting AI adoption, but governments are typically slow. Therefore, the authors plead for more direct government involvement. Legislation and willingness to stimulate development through public research, education and joint ventures (and possibly even subsidies) are strong levers a government can call upon to help promote this path.
However, governments may make use of new technology to gain more societal control. Although some use cases appear perfectly acceptable (e.g., standardizing unique identifiers across silos such as taxes and health), many questionable practices may emerge too. Population monitoring and control at the individual level via face recognition—for example, via social monitoring or in advertising—come to mind. The emergence of this new technology allows for new ways to infringe on privacy, possibly even on human freedom, especially when in governmental hands.
One last area in which governments bear a strong responsibility is to prepare for the job loss in companies providing routine, mundane activities. Several “compensation” ideas, such as universal basic income or universal minimum dividends schemes, through which governments yield a minimum income to every citizen irrespective of their job situation, have been considered for mitigating the effects of this job loss.
The final chapter deals with preparing children for this new IT-driven world, and the authors´ recommendations make good sense to this reviewer. These relevant, albeit largely non-controversial, recommendations are as follows:
Creativity
Coding
Communication
Confidence
In the brief conclusion, the authors reiterate that humans ultimately are in control. The human experience with any new technology, including AI, remains the centerpiece. Core ethical issues still need to be worked out, and our understanding of how decision-making will be impacted will need to be revised continually.
So, what is the relevance of this book to business people? Why should busy executives read it? In this reviewers’ view, the answer is clear: The book gives practitioners a good overview of what the new wave of IT generally entails, above all concerning AI. Demystification is at the core of such an effort. The authors indeed help the reader to understand how to make use of this new technology. All of us in the Lorange Network are active in business, and we often struggle to make our businesses less asset-intensive. The AI Republic is particularly relevant for achieving this goal.
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