A Human’s Guide to Machine Intelligence: A book review by Bob Morris

A Human’s Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in Control
Kartik Hosanagar
Viking (March 2019)

How we can ensure that algorithms serve us rather than enslave us

As I have indicated in several previous blog posts, I am convinced that most of the best career opportunities will be in the fields of alternative energies, and, in AI collaborations with machines. These opportunities are suggested in recently published books such as Paul Daugherty and H. James Wilson’s Human + Machine: Reimagining Work in the Age of AI, Thomas Davenport’s The AI Advantage: How to Put the Artificial Intelligence Revolution to Work, and Ajay Agrawal’s Prediction Machines: The Simple Economics of Artificial Intelligence. Add Kartik Hosanagar’s book to that list.

These opportunities will not be “low-hanging fruit,” passively waiting to be plucked. Rather, to obtain them, it will be necessary to be fully prepared (i.e. qualified) to fill the given position.  Hence the imprtance of the material now available.

For example, in Possible Minds, edited by John Brockman, Daniel Dennett shares his ideas about using AI to produce the mechanisms with which humans will collaborate most effectively: “So what we are creating are not — should not be — conscious humanoid agents but an entirely new sort of entity, rather like oracles, with no conscience, no fear of death, no distracting loves and hates, no personality (but all sorts of foibles and quirks that would no doubt be identified as the ‘personality’ of the system).”

Hosanagar provides a wealth of information, insights, and suggestions that will help those who read it to understand how and why humans must control — rather than be controlled by — algorithms. He observes, “When you think of the word ‘algorithm,’ you might picture a computer crunching numbers according to a formula. But stated quite simply, an algorithm is merely a series of steps one follows to get something done. For example, I follow a series of steps when I make an omelet. You might call it an omelet recipe, but the former engineer in me views it as an omelet algorithm.”

People will be needed to create or revise algorithms. Many more will be needed to implement, maintain, and improve (in collaboration with machines) the “series of steps one follows to get something done.” Hosanagar cites hundreds of real-world situations in which algorithms — under human supervision — increase and improve productivity in ways and to an extent otherwise impossible.

These are among the passages that caught my eye, also listed to suggest the scope of Hosanagar’s coverage:

o Algorithms (Pages 5-11 and 14-18)
o Neural networks (13-14, 88-89, 93-95, and 93-95)
o Algorithmic “Bill of Rights” (Pages 16-17 and 205-224)
o Decision making algorithms (26-27, 36-37, 54-55, and 230-231)
o Music services (62-68 and 134-135)

o Collaborative filtering (63-67)
o Programming of algorithms (59-81)
o Artificial intelligence (83-99)
o Machine learning (91-95, 98-99, and 116-118)
o Diagnostics in medicine (95-97, 98-99, 158-163, and 181-184)

o Go (101-106)
o Predictable systems (107-111)
o Big Data (119-121)
o Psychology of algorithms (125-142)
o Robo-advisers for investments (148-149 and 151-154)

o Control (165-180)
o Transparency (181-204)
o Grading of academic material such as exams (184-192)
o René Kizilcec (187-191)
o Games (225-234)

Those who share my high regard for this book are urged to check out each of the aforementioned sources. The career opportunities really are almost unlimited, not only for technicians but also for those who supervise them — at all levels and in all areas — while ensuring that AI initiatives are in proper alignment with the strategic objectives of the given enterprise.

Congratulations to Kartik Hosanagar on this brilliant achievement. Bravo!


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