By Tan Liong Choon, Senior Lecturer & Consultant, Digital Products & Platforms Practice, NUS-ISS
AI vs Jobs – Boon or Bane?
Gerd Neonhard is a well-known futurist, keynote speaker, author and CEO of The Futures Agency.
In his blog post of Nov 2015¹, he wrote about the online magazine Edge² and their annual poll of scientists, technologists, writers and academics for their response to a single question in 2013, “What Should* We Be Worried About?” (*that doesn’t seem to be on popular radar yet). I have sampled Digital Technology-related responses to this question from some of the most well known experts and thinkers in their fields.
- Misplaced worries from being swamped by the volume, novelty, speed of arrival, and complexity of ever-accelerating scientific and technological revolution. The result may be doing more harm than good. – Dan Sperber, Social and Cognitive Scientist; CEU Budapest and CNRS Paris; Co-author (with Deirdre Wilson), Meaning and Relevance; and (with Hugo Mercier), The Enigma of Reason
- That the internet is ruining writing. – David Gelernter, Computer Scientist, Yale University; Chief Scientist, Mirror Worlds Technologies; Author, America-Lite: How Imperial Academia Dismantled our Culture (and ushered in the Obamacrats)
- That opinions of search engines is becoming also the arbiters of truth. – W. Daniel Hillis, Physicist, Computer Scientist, Co-Founder, Applied Invention.; Author, The Pattern on the Stone
- Not Enough Robots. – Rodney A. Brooks, Panasonic Professor of Robotics (emeritus); Former Director, MIT Computer Science and Artificial Intelligence Lab (1997-2007); Founder, CTO, Robust.AI; Author, Flesh and Machines
- That we won’t make use of the Error Catastrophe Threshold, the threshold whereby the virus’ ability to replicate is not replicated, and so renders it extinct. – William McEwan, Investigator Scientist, MRC Laboratory of Molecular Biology, Cambridge, U.K. (**this last one is not exactly digital technology-linked but was added to my sampling list to reflect on the current “Black Swan” event that is gripping the world. Incidentally, Nassim Nicholas Taleb, author of The Black Swan offer his response to the question too.)
And what about Gerd himself?
He simply posted the following image with a little caption, “Laying off” :)
My perspective of his response is; he may have intended it as a tongue-in-cheek response even though I do agree that AI will translate to displacement of a significant number of jobs. AI-powered Robots is now ready to replace human language translators. Machine learning powered X-ray reader has shown to be able to match, and in some cases, surpass the accuracy of trained radiologists. Imagine a city where all cars are driverless and can be expected to act rationally according to clear traffic rules (unlike we mortal humans), traffic cops as we know it today, will be irrelevant.
Fast forward 5 years and we are already in the cusp of the AI revolution that is affecting all industries and fields of human activity. Prophets of doom has been predicting massive loss of job and mass unemployment. While it may sound ominous to some people, the opposite may be true.
In the World Economic Forum (WEF)’s The Future of Jobs Report 2018, by 2022, machines and algorithms will on average increased their contribution to specific tasks by 57% relative to 2018! However, the report also highlighted a net positive outlook for jobs even as machines and AI is starting to replace human tasks.
“Across all industries, by 2022, growth in emerging professions is set to increase their share of employment from 16% to 27% (11% growth) of the total employee base of company respondents, whereas the employment share of declining roles is set to decrease from currently 31% to 21% (10% decline). About half of today’s core jobs—making up the bulk of employment across industries—will remain stable in the period up to 2022.” – WEF
You can view the full report here.
Emergence of the AI Product Manager
So what does it mean for Product Managers and Product Management? I believe Digital Product Managers and the Product Management discipline are well-positioned to capitalise on the potential wealth of opportunities that may be opening up by the still evolving technology field; AI. In fact, product management is not just expanding; it is evolving with new roles like the AI Product Manager. The strategic nature of the product manager’s role puts him in the vital position to help organisations exploit and drive AI adoption. Big tech giants like Google, Amazon and Facebook are already competing through increasing the use of AI in their product offerings ranging from virtual smart assistant to personalised recommender of products and services such as Facebook expanding into dating services.
As more practitioners and AI-powered product innovations reach industry scale commercialisation, it may be worthwhile to establish a standard methodology and best practice for managing AI-powered products. At present, one good resource to start with is the AI Transformation Playbook by Andrew Ng, Founder and CEO of Landing AI, Founder DeepLearning.ai, and former lead of Google Brain team and Baidu AI Group.
In his AI Transformation Playbook³, Andrew recommended the following systematic steps to building AI product management capability as summarised below:
- Execute pilot projects to gain momentum
- Build an in-house AI team
- Provide broad AI training
- Develop an AI strategy
- Develop internal and external communications
That brings us to the next question. At this point, where is the most potential for AI and Machine Learning? A promising starting point would be Healthcare (nothing to do with Covid19!) Take the X-ray medical imaging. Everyone of us would have taken a few in our lifetime, not just when we are trying to diagnose a sickness but also to prove we are well (e.g. in hiring health screening). The WEF’s article on Sustainability Impact Summit highlighted that “at least half the world’s population still lacks access to essential health services.”⁴ The market scope is huge.
BusinessWire.com reported that the global healthcare market reached a value of nearly $8.4 Trillion in 2018, and is expected to grow to nearly $11.9 Trillion by 2022⁵.
In term of market volume and financial opportunities, this will be key priority for businesses in the immediate future and beyond.
A look at the National Health Expenditure Projections 2018-2027 Forecast Summary⁶ provide a sense of the financial scale of healthcare expenditure.
Major Findings for National Health Expenditures: 2018-2027. Under current law, national health spending is projected to grow at an average rate of 5.5 percent per year for 2018-27 and to reach nearly $6.0 trillion by 2027.
Two years into the Sustainable Development Goals era, global spending on health continues to rise. It was US$ 7.8 trillion in 2017, or about 10% of GDP and $1,080 per capita – up from US$ 7.6 trillion in 2016.
Just like Rodney Brooks’ response to The Edge’s annual poll back in 2013, the worry is Not Enough Robots. Today, we will be talking about both the hard (physical robots/cobots) and soft (software robot) kind and the worry is still - Not Enough Robots. The still emerging innovative adoption of Emotion AI (also known as facial coding) and social robots will open up new markets for the whole suite of healthcare business.
Are you currently working on such AI product research and development in your sphere of business or has launched such products recently? What are your experience and predictions? What are some essential skills specific to management of AI product development?
What about potential risk considerations, just to name a few below:
- How would you handle the ethics part of AI in products? (e.g. algorithm to give priority to rich customer, or allocate ventilator to the rich patient)
- Would security be an important part of your product design? (hackers can hijack your robo customer representative to spout vulgarities)
- Would resilience be an important design consideration (e.g. when AI advisor is down)?
Share your thoughts.
Writer, Liong Choon, is the Senior Lecturer & Consultant of Digital Products and Platforms, at the Institute of Systems Science, NUS (NUS-ISS). For more information on product management training, please click here.
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¹"The 150 things the world's smartest people are afraid of (some nice quotes here)."Futuristgerd.com. November. 2015. Web. 5 April 2020.
²Miller Geoffrey. "2013: What should we be worried about". Edge.org. 2013. Web. 6 April 2020.
³"AI Transformation Playbook. How to lead your company into the AI era."Landing.ai. 2020. Web. 6 April 2020.
⁴Mcneill Kirsty and Corry Jacobs. "Half of the world's population lack access to essential health services - are we doing enough?". Weforum.org. September 2019. Web. 6 April 2020.
⁵"The $11.9 trillion global healthcare market: key opportunities & strategies (2014-2022)." Businesswire.com. June 2019. Web. 7 April 2020.
⁶"Global spending on health: a world in transition." Who.int. 2019. Web. 8 April 2020.
Other references:
Skomoroch Peter and Mike Loukides. "What you need to know about product management for AI". Oreilly.com. March 2020. Web. 8 April 2020.
Dai W. David. "Can AI read chest x-rays like radiologists?" Towardsdatascience.com. June 2019. Web. 9 April 2020.