Technology

Free Webinar, Jan. 25: Practical and Ethical Aspects of Future Artificial Intelligence

Scott BuchananLeave a comment

As most of us know, artificial intelligence (AI) has taken big steps forward in the past few years, with the advent of Large Language Models (LLM) like ChatGPT. With these programs, you can enter a query in plain language, and get a lengthy response in human-like prose. You can have ChatGPT write a computer program or a whole essay for you (which of course makes it challenging for professors to evaluate essays handed in by their students).

However, the lords of Big Tech are not content. Their goal is to create AI with powers that far surpass human intelligence, and that even mimics human empathy. This raises a number of questions:

Is this technically possible? What will be the consequences if some corporations or nations succeed in owning such powerful systems? Will the computers push us bumbling humans out of the way? Will this be a tool for liberation or for oppression? This new technology coming at us may affect us all in unexpected ways. 

For those who are interested, there will be a 75-minute webinar on Saturday, January 25 which addresses these issues, and offers a perspective by two women who are leaders in the AI field (see bios below). They will explore the ethical and practical aspects of AI of the future, from within a Christian tradition. The webinar is free, but requires pre-registration:

https://network.asa3.org/events/EventDetails.aspx?id=1889760&group=

Here are bios of the two speakers:

Joanna Ng is a former IBM-er, pivoted to a start-up founder, focusing on Artificial Intelligence, specialized in Augmented Cognition, by integrating with IoT and Blockchain, in the context of web3, by applying design-thinking methodology. With forty-nine patents granted to her name, Joanna was accredited as an IBM Master Inventor. She held a seven-year tenure as the Head of Research, Director of the Center for Advanced Studies, IBM Canada. She has published over twenty peer-reviewed academic publications and co-authored two computer science books with Springer, The Smart Internet, and The Personal Web. She published a Christianity Today article called “How Artificial Intelligence Is Today’s Tower of Babel” and published her first book on faith and discipleship in October 2022, titled Being Christian 2.0.

Rosalind Picard is founder and director of the Affective Computing Research Group at the MIT Media Laboratory; co-founder of Affectiva, which provides Emotion AI; and co-founder and chief scientist of Empatica, which provides the first FDA-cleared smartwatch to detect seizures. Picard is author of over three hundred peer-reviewed articles spanning AI, affective computing, and medicine. She is known internationally for writing the book, Affective Computing, which helped launch the field by that name, and she is a popular speaker, with a TED talk receiving ~1.9 million views. Picard is a fellow of the IEEE and the AAAC, and a member of the National Academy of Engineering. She holds a Bachelors in Electrical Engineering from Georgia Tech and a Masters and Doctorate, each in Electrical Engineering and Computer Science, from MIT. Picard leads a team of researchers developing AI/machine learning and analytics to advance basic science as well as to improve human health and well-being, and has served as MIT’s faculty chair of their MindHandHeart well-being initiative.

Study Shows AI Can Enable Information-Stealing (Phishing) Campaigns

Scott BuchananLeave a comment

As a computer user, I make a modest effort to stay informed regarding the latest maneuvers by the bad guys to steal information and money. I am on a mailing list for the Malwarebytes blog, which publishes maybe three or four stories a week in this arena.

Here are three stories from the latest Malwarebytes email:

 ( 1 )   AI-supported spear phishing fools more than 50% of targets A controlled study reveals that 54% of users were tricked by AI-supported spear phishing emails, compared to just 12% who were targeted by traditional, human-crafted ones. ( 2 )  Dental group lied through teeth about data breach, fined $350,000 Westend Dental denied a 2020 ransomware attack and associated data breach, telling its customers that their data was lost due to an “accidentally formatted hard drive”. The company agreed to pay $350,000 to settle HIPAA violations ( 3 ) “Can you try a game I made?” Fake game sites lead to information stealers Victims lured to a fake game website where they were met with an information stealer instead of the promised game.

The first item here fits with our interest in the promise and perils of AI, so I will paste a couple of self-explanatory excerpts in italics:

One of the first things everyone predicted when artificial intelligence (AI) became more commonplace was that it would assist cybercriminals in making their phishing campaigns more effective.

Now, researchers have conducted a scientific study into the effectiveness of AI supported spear phishing, and the results line up with everyone’s expectations: AI is making it easier to do crimes.

The study, titled Evaluating Large Language Models’ Capability to Launch Fully Automated Spear Phishing Campaigns: Validated on Human Subjects, evaluates the capability of large language models (LLMs) to conduct personalized phishing attacks and compares their performance with human experts and AI models from last year.

To this end the researchers developed and tested an AI-powered tool to automate spear phishing campaigns. They used AI agents based on GPT-4o and Claude 3.5 Sonnet to search the web for available information on a target and use this for highly personalized phishing messages.

With these tools, the researchers achieved a click-through rate (CTR) that marketing departments can only dream of, at 54%. The control group received arbitrary phishing emails and achieved a CTR of 12% (roughly 1 in 8 people clicked the link).

Another group was tested against an email generated by human experts which proved to be just as effective as the fully AI automated emails and got a 54% CTR. But the human experts did this at 30 times the cost of the AI automated tools.

…

…The key to the success of a phishing email is the level of personalization that can be achieved by the AI assisted method and the base for that personalization can be provided by an AI web-browsing agent that crawls publicly available information.

Based on information found online about the target, they are invited to participate in a project that aligns with their interest and presented with a link to a site where they can find more details.

~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

But there is good news as well. We can use AI to fight AI: … LLMs are also getting better at recognizing phishing emails. Claude 3.5 Sonnet scored well above 90% with only a few false alarms and detected several emails that passed human detection. Although it struggles with some phishing emails that are clearly suspicious to most humans.

In addition, the blog article cited some hard evidence for year-over-year progress in AI capabilities: a year ago, unassisted AI was unable to match the phishing performance of human-generated phishing messages. But now, AI can match and even slightly exceed the effectiveness of human phishing. This is….progress, I guess.

P.S. I’d feel remiss if I did not remind us all yet again, it’s safest to never click on a link embedded in an email message, if you can avoid it. If the email purports to be from a company, it’s safest to go directly to the company’s website and do your business there.

No Tech Workers or No Tech Jobs?

Joy Buchanan1 Comment

Several recent tweets(xeets) about tech talent re-ignited the conversation about native-born STEM workers and American policy. For the Very Online, Christmas 2024 was about the H-1B Elon tweets.

Elon Musk implies that “elite” engineering talent cannot be found among Americans. Do Americans need to import talent?

What would it take to home grow elite engineering talent? Some people interpreted this Vivek tweet to mean that American kids need to be shut away into cram schools.

The reason top tech companies often hire foreign-born & first-generation engineers over “native” Americans isn’t because of an innate American IQ deficit (a lazy & wrong explanation). A key part of it comes down to the c-word: culture. Tough questions demand tough answers & if we’re really serious about fixing the problem, we have to confront the TRUTH:

Our American culture has venerated mediocrity over excellence for way too long (at least since the 90s and likely longer). That doesn’t start in college, it starts YOUNG. A culture that celebrates the prom queen over the math olympiad champ, or the jock over the valedictorian, will not produce the best engineers.

– Vivek tweet on Dec. 26, 2024

My (Joy’s) opinion is that American culture could change on the margin to grow better talent (and specifically tech talent) resulting in a more competitive adult labor force. This need not come at the expense of all leisure. College students should spend 10 more hours a week studying, which would still leave time for socializing. Elementary school kids could spend 7 more hours a week reading and still have time for TV or sports.

I’ve said in several places that younger kids should read complex books before the age of 9 instead of placing a heavy focus on STEM skills. Narratives like The Hobbit are perfect for this. Short fables are great for younger kids.  

The flip side of this, which creates the puzzle, is: Why does it feel difficult to get a job in tech? Why do we see headlines like “Laid-off techies face ‘sense of impending doom’ with job cuts at highest since dot-com crash” (2024)

Which is it? Is there a glut of engineering talent in America? Are young men who trained for tech frustrated that employers bring in foreign talent to undercut wages? Is there no talent here? Are H-1B’s a national security necessity to make up the deficit of quantity?

Previously, I wrote an experimental paper called “Willingness to be Paid: Who Trains for Tech Jobs?” to explore what might push college students toward computer programming. To the extent I found evidence that preferences matter, culture could indeed have some impact on the seemingly more impersonal forces of supply and demand.

For a more updated perspective, I asked two friends with domain-specific knowledge in American tech hiring for comments. I appreciate their rapid responses. My slowness, not theirs, explains this post coming out weeks after the discourse has moved on. Note that there are differences between the “engineers” whom Elon has in mind in the tweet below versus the broader software engineering world.

Software Engineer John Vandivier responds:

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Keeping Receipts

Zachary Bartsch1 Comment

Online shopping is convenient and even the norm for many items. Going to the store sounds like a time-consuming labor or an exceptional outing. My family, for example, lives in a suburban location that doesn’t have well-priced grocery home delivery. Shipping only works for some non-perishables. So, for many items we order online and do ‘drive-up pick-up’. We don’t even need to go into the store for many items. And reordering the same items repeatedly is a breeze.

We are also accustomed to the ability to return things. If your blender breaks on your first smoothie, then no worries – you can return it. If the chocolate cookies don’t taste like chocolate? Return it – satisfaction guaranteed. You can buy three pairs of shoes in different sizes and then keep the ones you want at the original sale price. Return the others.

For me, besides the time saved and convenience, a major factor in my decision to make purchases online is the documentation. I don’t need to save the receipt in a shoe box, Ziploc, or file drawer – the online retailer keeps an archive of all my purchases. Often this includes the date, amount, and shipping details including delivery date. There’s a super convenient digital paper trail.

If I need to contact a seller in order to exercise a warranty, then I have their contact information. I don’t need to retain the product packaging or investigate the brand at a future inopportune time. For example, I recently bought a Little Tykes water table for my kids. As I was assembling it on Christmas Eve I realized that I was missing a small part. I was able to work around it. But I was also able to immediately contact the manufacturer with a copy of my invoice. I emailed the date of purchase, the product model number, and the instruction manual had conveniently included part numbers. They were able to ship me the parts after a single email. Online shopping, and the resulting trail of evidence, makes the process much more practical than keeping paper records in a likely unorganized fashion.

There are other benefits to the paper trail. Back before widespread online shopping, retailers would often offer rebates as a sales strategy. In the year 2004, I bought a computer hard drive for $120 before a $40 mail-in rebate. The retailer (or manufacturer, I can’t remember) was hoping that people saw the post-rebate price and then failed to redeem it. And that often happened.  You needed to fill out a rebate form on an index card, cut the UPC bar code of the product packaging, and then mail them with your receipt to the company rebate department in a stamped envelope. If you dragged your feet, then you’d probably lose an important piece of the crucial combination and lose out on your $40 rebate. If the items were lost in the mail, then you were shucks-out-of-luck. Now, rebates have gone the way of the dodo since receipts are automatically retained and retrievable.

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Excel’s Weird (In)Convenience: COUNTIF, AVERAGEIF, & STDEVIF

Zachary Bartsch1 Comment

Excel is an attractive tool for those who consider themselves ‘not a math person’.  In particular, it visually organizes information and has many built-in functions that can make your life easier. You can use math if you want, but there are functions that can help even the non-math folks

If you are a moderate Excel user, then you likely already know about the AVERAGE and COUNT functions. If you’re a little but statistically inclined, then you might also know about the STDEV.S function (STDEV is deprecated). All of these functions are super easy and only have one argument. You just enter the cells (array) that you want to describe, and you’re done. Below is an example with the ‘code’ for convenience.

=COUNT(A2:A21)
=AVERAGE(A2:A21)
=STDEV.S(A2:A21)

If you do some slightly more sophisticated data analysis, then you may know about the “IF” function. It’s relatively simple; if a proposition is true (such as a cell value condition), then it returns a value. If the proposition is false, then it returns another value. You can even create nested “IF”s in which a condition being satisfied results in another tested proposition. Back when excel had more limited functions, we had to think creatively because there was a limit to the number of nested “IF” functions that were permitted in a single cell. Prior to 2007, a maximum of seven “IF” functions were permitted. Now the maximum is 64 nested “IF”s. If you’re using that many “IF”s, then you might have bigger problems than the “IF” limitations.

Another improvement that Excel introduced in 2019 was easier array arguments. In prior versions of Excel, there was some mild complication in how array functions must be entered (curly brackets: {}). But now, Excel is usually smart enough to handle the arrays without special instructions.  Subsequently, Excel has introduced functions that combine the array features with the “IF” functions to save people keystrokes and brainpower.

Looking at the example data we see that there is an identifier that marks the values as “A” or “B”. Say that you want to describe these subgroups. Historically, if you weren’t already a sophisticated user, then you’d need to sort the data and then calculate the functions for each subgroup’s array. That’s no big deal for small sets of data and two possible ID values, but it’s a more time-consuming task for many possible ID values and multiple ID categories.

The early “IF” statements allowed users to analyze certain values of the data, such as those that were greater than, less than, or equal to a particular value. But, what if you want to describe the data according to criteria in another column (such as ID)? That’s where Excel has some more sophisticated functions for convenience. However, as a general matter of user interface, it will be clear why these are somewhat… awkward.

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WSJ: Nothing Important Happened in China, India, or AI This Year

James Bailey3 Comments

I normally like the Wall Street Journal; it is the only news page I check directly on a regular basis, rather than just following links from social media. But their “Biggest News Stories of 2024” roundup makes me wonder if they are overly parochial. When I try to zoom out and think of the very biggest stories of the past five to ten years, three of the absolute top would be the rapid rise of China and India, together with the astonishing growth in artificial intelligence capabilities.

All three of those major stories continued to play out this year, along with all sorts of other things happening in the two most populous countries in the world, and all the ways existing AI capabilities are beginning to be integrated into our businesses, research, and lives. But the Wall Street Journal thinks that none of this is important enough to be mentioned in their 100+ “Biggest Stories”.

To be fair, China and AI do show up indirectly. AI is driving the 4 (!) stories on NVIDIA’s soaring stock price, and China shows up in stories about spying on the US, hacking the US, and the US potentially forcing a sale of TikTok. But there are zero stories regarding anything that happened within the borders of China, and zero that let you know that AI is good for anything besides NVIDIA’s stock price.

Plus of course, zero stories that let you know that India- now the world’s most populous country, where over one out of every six people alive resides- even exists.

AI’s take on India’s Prime Minister using AI

This isn’t just an America-centric bias on WSJ’s part, since there is lots of foreign coverage in their roundup; indeed the Middle East probably gets more than its fair share thanks to “if it bleeds, it leads”. For some reason they just missed the biggest countries. They also seem to have a blind spot for science and technology; they don’t mention a single scientific discovery, and only had two technology stories, on SpaceX catching a rocket and doing the first private spacewalk.

The SpaceX stories at least are genuinely important- the sort of thing that might show up in a history book in 50+ years, along with some of the stories on U.S. politics and the Russia-Ukraine war, but unlike most of the trivialities reported.

I welcome your pointers to better takes on what was important in 2024, or on what you consider to be the best news source today.

Humans are struggling to understand LLM Progress

Joy Buchanan1 Comment

Ajeya Cotra writes the following in “Language models surprised us” (recommended, with more details on benchmarks)

In 2021, most people were systematically and severely underestimating progress in language models. After a big leap forward in 2022, it looks like ML experts improved in their predictions of benchmarks like MMLU and MATH — but many still failed to anticipate the qualitative milestones achieved by ChatGPT and then GPT-4, especially in reasoning and programming.

Joy’s thoughts: A possible reason for underestimating the rate of progress is not just a misunderstanding of the technology but a missed estimate on how much money would get poured in. When Americans want to buy progress, they can (see also SpaceX).

I compare this to the Manhattan project. People said it couldn’t be done, not because it was physically impossible but because it would be too expensive.

After a briefing regarding the Manhattan Project, Nobel Laureate Niels Bohr said to physicist Edward Teller, “I told you it couldn’t be done without turning the whole country into a factory.” (https://www.energy.gov/lm/articles/ohio-and-manhattan-project)

We are doing it again. We are turning the country into a factory for AI. Without all that investment, the progress wouldn’t be so fast.

Joy on AI in Higher Education

Joy Buchanan1 Comment

I was interviewed for an article “Navigating AI in Christian Higher Education“. Here’s an excerpt:

Rosenberg: What impact do you foresee in your field due to the increasing sophistication of AI, and what kind of skills do you think your students will need to be successful?

Buchanan: AI will reshape economic analysis and modeling, making complex data processing and predictive analytics more accessible. This will lead to more sophisticated economic forecasting and policy design. Economists will become more productive, and expectations will rise accordingly. While some fields might resist change, economics will be at the forefront of AI integration.

For students aiming to succeed, it’s crucial to embrace AI tools without relying on them excessively during college. Strong fundamentals in economic theory and critical thinking remain essential, coupled with data science and programming skills.

Interdisciplinary knowledge, especially in tech and social sciences, will be valuable. Adaptability and lifelong learning are key in this evolving field. Human skills like creativity, communication, and ethical reasoning will remain crucial.

While AI will alter economics, it will also present opportunities for those who can adapt and effectively combine economic thinking with technological proficiency.

My Frozen Assets at BlockFi, Part 4: Full Recovery of My Funds

Scott Buchanan2 Comments

In March and April of this year, I moaned and groaned here in blogland, chronicling my attempts to recover my funds from an interest-bearing account at crypto firm BlockFi.

Back in 2021, interest rates had been so low for so long that that seemed to be the new normal. Yields on stable assets like money market funds were around 0.3% (essentially zero, and well below inflation), as I recall. As a yield addict, I scratched around for a way to earn higher interest, while sticking with an asset where (unlike bonds) the dollar value would stay fairly stable.

It was an era of crypto flourishing, and so I latched onto the notion of decentralized finance (DeFi) lending. I found what seemed to be a reputable, honest company called BlockFi, where I could buy stablecoin (constant dollar value) crypto assets which would sit on their platform. They would lend them out into the crypto world, and pay me something like 9 % interest. That was really, really good money back then, compared to 0.3%.

On this blog, I chronicled some of my steps in this journal. First, in signing up for BlockFi, I had to allow the intermediary company Plaid complete access to my bank account. Seriously, I had to give them my username and password, so they could log in as me, and not only be able to withdraw all my funds, but see all my banking transactions and history. That felt really violating, so I ended up setting up a small auxiliary bank account for Plaid to use and snoop to their heart’s content.

I did get up and running with BlockFi, and put in some funds and enjoyed the income, as I happily proclaimed (12/14/2021) on this blog, “ Earning Steady 9% Interest in My New Crypto Account “.

BlockFi assured me that they only loaned my assets out to “Trusted institutional counterparties” with a generous margin of collateral. What could possibly go wrong??

What went wrong is that BlockFi as a company got into some close relationship with Sam Bankman-Fried’s company, FTX.  Back in 2021-2022, twenty-something billionaire Sam Bankman-Fried (“SBF”) was the whiz kid, the visionary genius, the white knight savior of the crypto universe. In several cases, when some crypto enterprise was tottering, he would step in and invest funds to stabilize things. This reminded some of the role that J. P. Morgan had played in staving off the financial panics of 1893 and 1907. SBF was feted and lauded and quoted endlessly.

For reasons I never understood, BlockFi as a company was having a hard time turning a profit, so I think the plan was for FTX to acquire them. That process was partway along, when the great expose’ of SBF as a self-serving fraudster occurred at the end of 2022. FTX quickly declared bankruptcy, which forced BlockFi to go BK as well. SBF was eventually locked up, but so were the funds I had put into BlockFi. The amount was not enough to threaten my lifestyle, but it was enough to be annoying.

BlockFi Assets Begin to Thaw

I got emails from BlockFi every few months, assuring customers that they would do what they could to return our assets. Their bankruptcy proceedings kept things locked, but eventually they started to return some money.

 As I noted in a blog post, in April, 2024, I was able to recover about 27% of my account. At the time, there was no clear prospect of getting the rest.   Along the way, I clicked on a well-camouflaged scam email link, which gave me some heartburn but fortunately no harm came of it.

And now, hooray, they have finally returned it all, following their successful claw-back of assets from SBF’s organization(s). This vindicates my sense that the BlockFi management was/is fundamentally honest and good-willed, and was just a victim of SBF’s machinations.

Some personal takeaways from all this:

  • Keep allocations smallish to outlier investments
  • Sell out at the first serious signs of trouble
  • Triple-check before clicking on any link in an email
  • Having been forced to engage in opening crypto wallets and transferring coins, I have a better feel for the world of crypto which had seemed like a black box. It does not draw me like it does some folks, but if circumstances ever require me to deal in crypto (relocate to Honduras?), I could do it.

Can researchers recruit human subjects online to take surveys anymore?

Joy BuchananLeave a comment

The experimental economics world is currently still doing data collection in traditional physical labs with human subjects who show up in person. This is still the gold standard, but it is expensive per observation. Many researchers, including myself, also do projects with subjects that are recruited online because the cost per observation is much lower.

As I remember it, the first platform that got widely used was Mechanical Turk. Prior to 2022, the attitude toward MTurk changed. It became known in the behavioral research community that MTurk had too many bots and bad actors. MTurk had not been designed for researchers, so maybe it’s not surprising that it did not serve our purposes.

The Prolific platform has had a good reputation for a few years. You have to pay to use Prolific but the cost per observation is still much lower than what it costs to use a traditional physical laboratory or to pay Americans to show up for an appointment. Prolific is especially attractive if the experiment is short and does not require a long span of attention from human subjects.

Here is a new paper on whether supposedly human subjects are going to be reliably human in the future: Detecting the corruption of online questionnaires by artificial intelligence   

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