The future of AI as a threat to our jobs is a popular topic. Here is a book to help you respond.
Unlike so much that is written on this topic, Tony Boobier‘s latest book focuses on a positive response. It also investigates the implications of AI at a deeper level than most analysis.
While many books have been written that focus on explaining AI, or focusing on the technology, this book focuses on jobs. Tony includes extensive research and careful analysis. He takes us through most sectors, to understand opportunities and threats.
Let me explain why Tony’s book, “Advanced Analytics & AI“ is worth reading, both for your role now and as future career advice.
Never mind understanding AI; do you understand work?
Tony is a man who has read widely. His polymath nature really shines through the start of this book. The subtitle hints at the breadth he explores, “Impact, Implementation & The Future of Work.“
Rather than just focusing on AI, Tony usefully starts by exploring the history of work. From slavery to the “flat white economy,“ he engagingly muses on both our need for work and how we recognize and value our abilities. This mindset guides his later exploration.
He goes on to provide some useful definitions of analytics and AI, helpfully calling out the lack of clarity and misuse of both terms that abounds. From business intelligence to advanced analytics and prescriptive analytics, plus rules-based systems and cognitive analytics, Tony manages to understand the purist distinctions and be pragmatic about what matters.
Going on to define AI, with particular reference to the Turing test, Tony briefly walks us through the history of AI development. As someone who worked in AI before the “AI winter,“ I recognize many of his examples and why the recent renaissance might be different.
Learning from AI in leading-edge industries
His list of leading-edge industries is always going to be controversial. But, given the investments that I have seen, I think there’s a good case for his selection. It includes financial services, automobiles, media/entertainment/telco and retail.
This chapter begins what is the heart of this book. For each sector (e.g. insurance), Tony outlines the relevance of AI and how it might replace some of the work currently done by humans.
His analysis is pragmatic. He points out challenges, difficulties and where either consumers may not accept technology or where the risks are too great. Tony does identify useful opportunities for AI innovation. He also suggests where those working in that sector can still add value.
The detail provided on so many diverse roles is particularly impressive. This is a well-researched book and a result of many years working in some of these sectors. Tony is also pragmatic in his identification of applications. From robo-advice to automated cars or supply chains, he calls out real progress and work still to be done.
AI progress within second-mover industries
Given a media focus on AI within leading-edge industries (e.g. autonomous vehicles), it is interesting to look elsewhere. Reading through the previous chapter, it became obvious that a number of AI innovations should be transferable.
In this chapter, Tony reviews those sectors that are beginning to apply pilots based on the above successes. From construction to utilities, public sector and agriculture, he challenges us to see how widespread adoption of AI could transform these jobs.
From smart homes to connected infrastructure, predictive policing to automated harvesting, Tony presents a picture of not just a threat to jobs, but a different way of working, that has subtly different challenges for each sector.
His challenges to previously accepted hierarchies and divisions between sectors are also important. With automated delivery of supply chains, previously separate industries could merge in new ways, one of many indications of the need for creative thinking by leaders.
The future of AI and its impact on professions
My own experience of seeking to get offshoring of analytics to work has taught me to be skeptical of hype. At the time, many commentators predicted the offshoring of white collar jobs. This proved limited, as the model ended up only working well for well-prescribed, repeatable processes.
We have also been this way before with AI. As Tony mentions, the hey day of expert systems in the 1990s predicted at least decision support for many professional roles, hopes that withered during the AI winter.
So, I read Tony’s chapter on the impact of AI on professional roles with some skepticism. That said, he does make a convincing case across a much wider range of professions than many would consider, not just to doctors, teachers and lawyers. Tony highlights the implications for AI delivering management, finance, engineering and even creative roles.
At the very least, Tony makes the case for opportunities and uncertainty – as a challenge for managers and entrepreneurs in this space. The role AI could play is still only starting to be defined for most professions, and planning would help.
Let’s stop pretending data science and AI are risk-free
Apart from extreme predictions of the end of humanity in robot wars, many articles suggest the rise of AI will be smooth. One might think it was risk-free and in line with the continual improvement of the human condition, even though so much that has gone wrong already should cause us to be circumspect.
Tony rightly includes a chapter summarizing these risks, from system failures to data privacy, employee error to reputational risk. Considering the role of the maturing regulation technology (regtech) sector, it is clear that does not provide all the answers.
Risk management, as for other sectors, needs a balance to be struck between automated efficiency and human judgment.
Prepare for your career in the future of AI
The most useful contribution of this book to society is the way that Tony ends it. In his final four chapters, Tony reviews:
- Potential AI implementation road maps
- New business models (made possible by AI)
- Coping with the future (societal considerations)
- Strategies for personal reinvention
