AI: Big Ideas and Bigger Challenges for the Next Quarter Century. Maybe, Maybe Not
February 13, 2024
This essay is the work of a dumb dinobaby. No smart software required.
I read an interesting ArXiv.org paper with a good title: “Ten Hard Problems in Artificial Intelligence We Must Get Right.” The topic is one which will interest some policy makers, a number of AI researchers, and the “experts” in machine learning, artificial intelligence, and smart software.
The structure of the paper is, in my opinion, a three-legged stool analysis designed to support the weight of AI optimists. The first part of the paper is a compressed historical review of the AI journey. Diagrams, tables, and charts capture the direction in which AI “deep learning” has traveled. I am no expert in what has become the next big thing, but the surprising point in the historical review is that 2010 is the date pegged as the start to the 2016 time point called “the large scale era.” That label is interesting for two reasons. First, I recall that some intelware vendors were in the AI game before 2010. And, second, the use of the phrase “large scale” defines a reality in which small outfits are unlikely to succeed without massive amounts of money.
The second leg of the stool is the identification of the “hard problems” and a discussion of each. Research data and illustrations bring each problem to the reader’s attention. I don’t want to get snagged in the plagiarism swamp which has captured many academics, wives of billionaires, and a few journalists. My approach will be to boil down the 10 problems to a short phrase and a reminder to you, gentle reader, that you should read the paper yourself. Here is my version of the 10 “hard problems” which the authors seem to suggest will be or must be solved in 25 years:
- Humans will have extended AI by 2050
- Humans will have solved problems associated with AI safety, capability, and output accuracy
- AI systems will be safe, controlled, and aligned by 2050
- AI will make contributions in many fields; for example, mathematics by 2050
- AI’s economic impact will be managed effectively by 2050
- Use of AI will be globalized by 2050
- AI will be used in a responsible way by 2050
- Risks associated with AI will be managed by effectively by 2050
- Humans will have adapted its institutions to AI by 2050
- Humans will have addressed what it means to be “human” by 2050
Many years ago I worked for a blue-chip consulting firm. I participated in a number of big-idea projects. These ranged from technology, R&D investment, new product development, and the global economy. In our for-fee reports were did include a look at what we called the “horizon.” The firm had its own typographical signature for this portion of a report. I recall learning in the firm’s “charm school” (a special training program to make sure new hires knew the style, approach, and ground rules for remaining employed at that blue-chip firm). We kept the horizon tight; that is, talking about the future was typically in the six to 12 month range. Nosing out 25 years was a walk into a mine field. My boss, as I recall told me, “We don’t do science fiction.”
The smart robot is informing the philosopher that he is free to find his future elsewhere. The date of the image is 2025, right before the new year holiday. Thanks, MidJourney. Good enough.
The third leg of the stool is the academic impedimenta. To be specific, the paper is 90 pages in length of which 30 present the argument. The remain 60 pages present:
- Traditional footnotes, about 35 pages containing 607 citations
- An “Electronic Supplement” presenting eight pages of annexes with text, charts, and graphs
- Footnotes to the “Electronic Supplement” requiring another 10 pages for the additional 174 footnotes.
I want to offer several observations, and I do not want to have these be less than constructive or in any way what one of my professors who was treated harshly in Letters to the Editor for an article he published about Chaucer. He described that fateful letter as “mean spirited.”
- The paper makes clear that mankind has some work to do in the next 25 years. The “problems” the paper presents are difficult ones because they touch upon the fabric of social existence. Consider the application of AI to war. I think this aspect of AI may be one to warrant a bullet on AI’s hit parade.
- Humans have to resolve issues of automated systems consuming verifiable information, synthetic data, and purpose-built disinformation so that smart software does not do things at speed and behind the scenes. Do those working do resolve the 10 challenges have an ethical compass and if so, what does “ethics” mean in the context of at-scale AI?
- Social institutions are under stress. A number of organizations and nation-states operate as dictators. One central American country has a rock star dictator, but what about the rock star dictators working techno feudal companies in the US? What governance structures will be crafted by 2050 to shape today’s technology juggernaut?
To sum up, I think the authors have tackled a difficult problem. I commend their effort. My thought is that any message of optimism about AI is likely to be hard pressed to point to one of the 10 challenges and and say, “We have this covered.” I liked the write up. I think college students tasked with writing about the social implications of AI will find the paper useful. It provides much of the research a fresh young mind requires to write a paper, possibly a thesis. For me, the paper is a reminder of the disconnect between applied technology and the appallingly inefficient, convenience-embracing humans who are ensnared in the smart software.
I am a dinobaby, and let me you, “I am glad I am old.” With AI struggling with go-fast and regulators waffling about go-slow, humankind has quite a bit of social system tinkering to do by 2050 if the authors of the paper have analyzed AI correctly. Yep, I am delighted I am old, really old.
Stephen E Arnold, February 13, 2024
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