Over the past year, you’ve likely seen and heard (or plane used) something involving strained intelligence (AI). There has been wide speculation well-nigh how this technology might stupefy humanity and many important questions have been raised. Is AI a hype cycle? Is it the next industrial revolution? Or is it science fiction come to life to upend life as we know it?
This is the first in a series of blog posts looking closer at AI, in particular what it ways for your portfolio, and what it could midpoint for our overall future. If you’re unfamiliar with AI or new to what it can offer, I’ll moreover be introducing you to some of my favorite AI tools withal the way.
American Productivity in Decline
First, a unenduring anecdote. I was riding horses on a upper mountain trail in Montana with a Treasury Department Deputy Assistant Secretary. He wasn’t the Fed Chairman or anything like that, but this Harvard educated economist was the weightier vacation friend an economics nerd like me could possibly have met.
It was one of those small world moments, too. We pieced together how he was once good friends with my cousin from Short Hills. Coincidences aside, we talked well-nigh the national debt, the coming explosion of entitlement expenses (e.g. Medicare), and a puzzling lull in productivity growth.
Cowboy hats. Big sky. Economics. I was in heaven – except for our conclusion: America needed productivity to giddyup up, and fast. Eight years without that vacation, it still has not. And we veritably need stronger productivity gains to stave raising taxes or wearing entitlement benefits.
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Enter AI
We have unquestionably seen strained intelligence coming at us for a while. While short-term market moves are still (and likely unchangingly will be) a murky business, there are plenty of examples to support the notion that long-term trends can be observed in advance, if not their full significance. People saw climate transpiration coming, right?
In 1896, Swedish scientist Svante Arrhenius predicted the greenhouse effect. Old Svante didn’t know the word-for-word contours or implications of his observation. But he was worldly-wise to predict that industrial emissions of stat dioxide were significant unbearable to rationalization global warming. If Svante had ripened an investment thesis to profit from that observation, he may well have fallen unappetizing on his face. But the point is, some macro trends are observable plane if the word-for-word contours of their economic implications remain mysterious.
In 1965, Gordon Moore predicted the coming exponential growth in computing power in tandem with an equal but opposite swoon in prices. What came to be known as Moore’s Law – the doubling in silicon-based computing power paired with a halving of prices every two years – has held up, with only some slowing in the past decade or so. Point is, Moore moreover saw the trend.
Ray Kurzweil, flipside futurist, saw the same trends in computing and made a number of prescient predictions as early as 1990, including pocket-sized personal digital assistants, deject computing, voice recognition, drones, universal translation, and streaming. Not bad.
In 1999, Ray predicted The Singularity. The Singularity refers to the moment strained general intelligence (AGI) exceeds human intelligence, sparking rapidly progressive technological progress vastitude human tenancy virtually 2045. Fun! Ray now says 2099. Pheew? Maybe he just extrapolated too far. But the idea of machine intelligence is quite old. Rene Descartes contemplated intelligent machines in 1637. Since then, the pace of AIs emergence (in our consciences at least) keeps accelerating:
- In 1950, Alan Turing devised a test to identify machine intelligence
- The Terminator first screened in 1984. I was 13 and impressionable
- In 2011, IBM’s Watson won a champions’ tournament on Jeopardy
- In January of 2023, ChatGPT-3.5 took, but failed, the bar exam
- In March of 2023, ChatGPT-4.0 passed the bar exam, scoring in the 90th percentile
The Risks of Present Day AI
Have machines passed Turing’s test? Can computers fool humans to think they are interacting with a human? While no one thinks we are on the cusp of AGI, the dangers of AI are stuff taken seriously by those sitting in the rooms where AI is happening.
In May, the Center for AI Safety released this starkly unenduring statement:
“Mitigating the risk of extinction from AI should be a global priority slantingly other societal-scale risks such as pandemics and nuclear war.”
The statement was signed by 350 leading merchantry and engineering minds working in strained intelligence including Sam Altman, the CEO of OpenAI, the visitor responsible for the ChatGPT chatbot that got everybody talking in late 2022.
I do think something is coming.
Like nuclear power, it holds both promise and peril. It certainly has society’s attention. Google searches for ‘artificial intelligence’ have increased significantly since the fall of 2022. Plane I, while writing this article, used AI to momentarily offset talk of societal-scale risks with a little whimsy. I prompted my favorite AIs to “Write a haiku well-nigh AI taking over human jobs.”
Haiku by Open AI’s ChatGPT-4.0
Jobs in silicon hands,
Human tasks in circuit’s dance,
Echoes of progress.
Haiku by Anthropic’s Claude.ai
Silicon brains grow fast
Human roles soon obsolete
Machines now in charge
Haiku by Google’s Bard
The machine is fast
It works without rest or pay.
Where will we all go?
Before you despair, note Claude’s uneaten syllable in the first line of the haiku. Well, you could pronounce it Sil-con. Despair!
Or consider the tale of the lawyer who found himself in hot water with a judge without relying on ChatGPT to research a legal brief. The cases he cited were entirely made-up by AI. Convincing but nonexistent, the citations ChatGPT returned were formatted correctly and plane ‘written’ in the style of very judges. They were fiction.
Your Honor was not pleased.
Tips to Stave AI Mistakes
The fault, in fairness, lies with the lawyer.
OpenAI discloses that, “ChatGPT may produce inaccurate information well-nigh people, places, or facts.” ChatGPT pointed that out to me when I asked it to critique this post for factual inaccuracies. Decent point! Lawyers are supposed to read the fine print.
Chatbots, it turns out, are prone to ‘hallucinate.’
The large language models on which they rely on are simply using probability to predict the next word. Large language models primarily make it ‘sound right’. I commonly find inaccuracies and won’t rely on AI answers without cross-referencing them. Don’t expect logic or reasoning. And confirm, confirm, confirm.
So, is AI overhyped or are we on the cusp of revolutionary change?
Yes and yes.
Amara’s Law states that in the short term we overestimate new technologies. In the long term, we underestimate them. Using the internet as a metaphor, we are using dial-up modems today.
ChatGPT thinks I am overstating our current lack of sophistication and insight. “The illustration ‘Using the internet as a metaphor, we are using dial-up modems today’ could be misleading. While it’s true that we are in the early stages of leveraging AI technologies, it might imply that our current understanding and usage of AI is slower or less sophisticated than it unquestionably is.”
Typical AI.
It certainly seems intelligent. It makes you wonder what underlies our intelligence?
Regardless, the potential creative destruction of AI use could be on par with our country’s transition from wild to industrial which saw the share of Americans working on farms waif from 72% to less than 2%. That would be very disruptive to some workers like lawyers (or plane financial advisors). But it is nonflexible to oppose that we are materially worse off today than we were surpassing tractors. It’s these types of tradeoffs that will likely pinpoint the financial future.
AI and Your Investment Portfolio
So, what does AI midpoint for your investment portfolio? (That’s probably why you’re still reading this.) Strained intelligence still pales in comparison to the informational content of the market’s AI – volume intelligence. All information known by all investors is reflected in market prices through the process of ownership and selling hundreds of billions of dollars worth of securities every day. The data-informed financial models driving those trading decisions are not misogynist on the unshut internet and so not misogynist to AI.
That is not to say that zippy investors have not employed AI processes for years in hopes of gleaning an informational edge. By scraping text from financial reports or gauging social media sentiment, they aim to identify stocks set to outperform. Any material insights they might note are quickly reflected in market prices. As increasingly investors employ the same tools, any unenduring wholesomeness diminishes.
Most damningly for those who might fantasize well-nigh outsmarting markets, AI’s forecasting prowess requires stable patterns. My phone’s navigation app recognizes my commute to work considering it follows a routine. Autonomous vehicles halt for familiar stop signs. But stock markets transpiration day to day in ramified and dynamic ways. AI trying to predict market prices is like self-driving cars trying to read stop signs with words, shapes, and colors that differ from one day to the next.
AI will scrutinizingly certainly protract to enhance investment processes and its impact will go well vastitude the financial sector. McKinsey’s June 2023 report entitled The Economic Potential of Generative AI: The Next Productivity Frontier exclaims, “Our latest research estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually wideness the 63 use cases we analyzed – by comparison, the United Kingdom’s unshortened GDP in 2021 was $3.1 trillion.”
The tl/dr version: McKinsey predicts AI will be worth a G-7 country, annually.
AI and Your Financial Future
It does not take much intelligence, strained or human, to imagine how AI could uplift productivity, economic growth, and your portfolio. Or we may all be pets to the machines one day. Who knows? Like all good financial advisors, we will watch, learn, and plan accordingly.
ChatGPT critiqued my last paragraph:
“Lastly, the whimsical note well-nigh ‘we may all be pets to the machines one day’ is a popular trope in discussions well-nigh AI, but it’s worth stressing that this is a far-fetched scenario based on speculation, not on current AI capabilities or trends. Plane with advances in AI, there are significant challenges and upstanding considerations involved in developing machines with that level of autonomy and power.”
If you say so, ChatGPT.
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