Jeffrey Funk
Are Good Ideas Hard to Find?
This academic paper tells us a lot about why innovation has slowed
When it Comes to New Technologies Like AI, Tempers Run Hot
So far, the most tangible LLM successes have been in generating political disinformation and phishing scams.
How Do We Define Successful Use Cases for Generative AI?
Current generative AI systems are designed to give us the most common solutions, instead of the new ones we need.
Productivity Increase Will Take Time in the Age of AI
An acceleration in productivity growth from AI isn’t right around the corner, despite promises by economists.
Why Are We Obsessed With How Smart AI Is?
The people with the most specific knowledge should be assessing applications for AI and their risks.
When will the AI-driven Productivity Revolution Begin?
Big corporations are slow to embrace AI tech
The LK-99 BS Further Undermines the Credibility of Science
The rejection or distortion of genuine science can have tragic consequences
Using Data Like a Drunk Uses a Lamppost
Startup companies can be tempted to use statistics for support instead of real illumination
Scientists Have Been Recommending Changes to Science Education for Decades
The modern education system seems designed to squelch curiosityGary Smith describes the problems with today’s science in his new book Distrust: Big Data, Data-Torturing, and the Assault on Science. He recounts endless examples of disinformation, data torture, and data mining, much of which we already knew. Taken together, however, and as I described in this review, they are mind-blowing. He argues that many of these problems come from things scientists do such as p-hacking during statistical analysis, too little emphasis on “impact” in statistical analyses, outright data falsification, and the creation of the Internet, which can be a huge disinformation machine in addition to a valuable resource. In the last chapter, he also offers some solutions such as ending the artificial thresholds for p-values such as 0.05, requiring Read More ›
Review of Distrust: Big Data, Data-Torturing, and the Assault on Science
Tech expert Jeffrey Funk reviews Gary Smith's enlightening new book on data, disinformation, and the "assault on science"The pandemic proved a lot of things, one of them being that science is under assault. In this enlightening and entertaining new book, Professor Gary Smith shows us how much of the assault has its roots in what scientists do. The easiest impact to understand is the Internet, which was originally created by scientists in the 1970s to exchange scientific information. Now it has become a great way to spread disinformation on almost every subject. A former chief historian of NASA noted that: “The reality is, the internet has made it possible for people to say whatever the hell they like to a broader number of people than ever before.” Smith recounts endless examples of this disinformation, much of which Read More ›
Review of “Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity”
This new book on tech, AI, and economic prosperity by Daron Acemoglu and Simon Johnson is incredibly timelyThis book by two MIT economists is very timely because the world is now dealing with the latest in the “Thousand Year Struggle,” in the form of artificial intelligence, the claims that many white-collar jobs will be automated, OpenAI’s call for regulation, and the possibility that AI will bring a further concentration of power among the big tech companies. Much of the book sets the stage for this discussion by summarizing the history of technology. This review focuses on the economic and social impact of automation and information technology over the last 50 years. For instance, “the distribution of income between capital and labor began to change significantly in the late 20th century. While throughout most of the century, about Read More ›
A World Without Work? Here We Go Again
Large language models still can't replace critical thinkingOn March 22, nearly 2,000 people signed an open letter drafted by the Future of Life Institute (FLI) calling for a pause of at least 6 months in the development of large language models (LLMs): Contemporary AI systems are now becoming human-competitive at general tasks, and we must ask ourselves: Should we let machines flood our information channels with propaganda and untruth? Should we automate away all the jobs, including the fulfilling ones? Should we develop nonhuman minds that might eventually outnumber, outsmart, obsolete and replace us? Should we risk loss of control of our civilization? FLI is a nonprofit organization concerned with the existential risks posed by artificial intelligence. Its president is Max Tegmark, an MIT professor who is no stranger to hype. Read More ›
Does New A.I. Live Up to the Hype?
Experts are finding ChatGPT and other LLMs unimpressive, but investors aren't getting the memoOriginal article was featured at Salon on February 21st, 2023. On November 30, 2022, OpenAI announced the public release of ChatGPT-3, a large language model (LLM) that can engage in astonishingly human-like conversations and answer an incredible variety of questions. Three weeks later, Google’s management — wary that they had been publicly eclipsed by a competitor in the artificial intelligence technology space — issued a “Code Red” to staff. Google’s core business is its search engine, which currently accounts for 84% of the global search market. Their search engine is so dominant that searching the internet is generically called “googling.” When a user poses a search request, Google’s search engine returns dozens of helpful links along with targeted advertisements based on its knowledge of the Read More ›
Goodhart’s Law and Scientific Innovation in Academia
Many university researchers are leaving academia so they can actually get things doneBritish economist Charles Goodhart was a financial advisor to the Bank of England from 1968 to 1985, a period during which many economists (“monetarists”) believed that central banks should ignore unemployment and interest rates. Instead, they believed that central banks should focus on maintaining a steady rate of growth of the money supply. The core idea was that central banks could ignore economic booms and busts because they are short-lived and self-correcting (Ha! Ha!) and should, instead, keep some measure of the money supply growing at a constant rate in order to keep the rate of inflation low and constant. The choice of which money supply to target was based on how closely it was statistically correlated with GDP. The Read More ›
Large Language Models Can Entertain but Are They Useful?
Humans who value correct responses will need to fact-check everything LLMs generateIn 1987 economics Nobel Laureate Robert Solow said that the computer age was everywhere—except in productivity data. A similar thing could be said about AI today: It dominates tech news but does not seem to have boosted productivity a whit. In fact, productivity growth has been declining since Solow’s observation. Productivity increased by an average of 2.7% a year from 1948 to 1986, by less than 2% a year from 1987 to 2022. Labor productivity is the amount of goods and services we produce in a given amount of time—output per hour. More productive workers can build more cars, construct more houses, and educate more children. More productive workers can also enjoy more free time. If workers can do in four Read More ›
Tech bubble? Our Progress Towards Value to Users Has Slowed…
We should be wary of glowing forecasts when newer technologies don’t offer anywhere near as large benefitsToday’s new technologies, from virtual reality to nuclear fusion have recently received record investments from venture capitalists, but their revenues are not growing as fast as technologies of past decades. Startup losses are unprecedented — far larger than in past decades. Share prices and private valuations have also been collapsing in 2022. Optimists mostly focus on the good news and ignore these facts. They believe that the heavy funding for these new technologies is a good measure of potential and thus any criticism is unjustified. Here is their typical argument: Paul Krugman and other “experts” criticized the Internet, personal computers, and other technologies in their early years. But these technologies succeeded. Therefore, criticisms of the new technologies are unfounded — Read More ›
The Hyper-Specialization of University Researchers
So many papers are published today in increasingly narrow specialties that, if there is still a big picture, hardly anyone can see itThe Bible warns that, “Of making many books there is no end; and much study is a weariness of the flesh.” Nowadays, the endless making of books is dwarfed by the relentless firehose of academic research papers. A 2010 study published in the British Medical Journal reported that the U.S. National Library of Medicine includes 113,976 papers on echocardiography — which would weary the flesh of any newly credentialed doctor specializing in echocardiography: We assumed that he or she could read five papers an hour (one every 10 minutes, followed by a break of 10 minutes) for eight hours a day, five days a week, and 50 weeks a year; this gives a capacity of 10000 papers in one year. Read More ›
How Far Will Unicorn Share Prices Fall?
Cumulative losses give us some insightsMost investors know that America’s Unicorns are losing money. What they don’t know is that most Unicorns have dug big holes for themselves and aren’t sure how to dig themselves out. What do I mean by holes? I mean massive cumulative losses that have been accumulated over many years of yearly losses. Because many of today’s Unicorn startups were founded at least 10 years ago, and are still unprofitable, they have a had a long time to create huge cumulative losses, some much more than the $3 billion that Amazon once had. The biggest losses are for Uber ($29.1 billion), WeWork ($12.2 billion), Snap ($8.7 billion), Lyft ($8.5 billion), Teledoc Health ($8.1 billion), and Airbnb ($6.4 billion), followed by four Read More ›
Is Rationality Finally Emerging for Unicorn Share Prices?
Share prices are falling as losses continue to mount2021 was a great year globally for venture capital and startups. Initial public offerings (IPOs) raised a record $594 billion in 2021 globally while VC funding is on track to hit a record $454 billion invested through the first three quarters of 2021.This is up from $332 billion for the first three quarters of 2020, which was the previous record for three quarters. U.S. startups also did well with big increases in both VC funding and IPOs in 2021. Almost $100 billion of funding was given to startups in the first three quarters while for the full year, there were 416 IPOs, of which 128 were from the tech section. The total amount raised was $156 billion, of which $69 billion was for the tech sector. Read More ›