AI Has Nothing To Do With Intelligence

AI has nothing to do with intelligence but people believe the marketing hype, mostly because we have a distorted idea of what intelligence is, largely due to the media.

Take the quiz show “Are You Smarter Than a Fifth Grader” that says in its name that it’s about whether contestants are as intelligent as a fifth grade student. What the show actually tests is who is more familiar with the grade five curriculum, grade five students or people who have not been in school for twenty tears or more. I know who I am betting on.

And take the famously super intelligent Jeopardy champions. Maybe some of these people are highly intelligent but that is not why they are Jeopardy champions because Jeopardy is not about intelligence. It is about knowing stuff, particularly the type of stuff Jeopardy asks questions about. At best it is about knowledge, not intelligence.

The Cambridge Dictionary defines intelligence as: “the ability to learn, understand, and make judgments or have opinions that are based on reason”. (Source)

I would refine that to: “the ability to understand and analyze information in order to make rational decisions based on that information”.

Intelligence is not about information it is about reasoning.

I remember what some might call the first forerunner to Alexa and other chat bots. It was called Eliza

ELIZA's creator, Weizenbaum, intended the program as a method to explore communication between humans and machines. He was surprised and shocked that individuals, including Weizenbaum's secretary, attributed human-like feelings to the computer program.[3] Many academics believed that the program would be able to positively influence the lives of many people, particularly those with psychological issues, and that it could aid doctors working on such patients' treatment.[3][13] While ELIZA was capable of engaging in discourse, it could not converse with true understanding.[14] However, many early users were convinced of ELIZA's intelligence and understanding, despite Weizenbaum's insistence to the contrary.[6] (Source)

This was not artificial intelligence and neither are the latest claimants, the large language models (LLMs).

A large language model (LLM) is a language model notable for its ability to achieve general-purpose language understanding and generation. LLMs acquire these abilities by learning statistical relationships from text documents during a computationally intensive self-supervised and semi-supervised training process.[1] LLMs are artificial neural networks following a transformer architecture.[2]

As autoregressive language models, they work by taking an input text and repeatedly predicting the next token or word.[3] Up to 2020, fine tuning was the only way a model could be adapted to be able to accomplish specific tasks. Larger sized models, such as GPT-3, however, can be prompt-engineered to achieve similar results.[4] They are thought to acquire knowledge about syntax, semantics and "ontology" inherent in human language corpora, but also inaccuracies and biases present in the corpora.[5]

Notable examples include OpenAI's GPT models (e.g., GPT-3.5 and GPT-4, used in ChatGPT), Google's PaLM (used in Bard), and Meta's LLaMA, as well as BLOOM, Ernie 3.0 Titan, and Anthropic's Claude 2. (Source)

Using statistics to mimic what a human might say or write is not reasoning and it is certainly not intelligence.

It might not be so bad if these systems did not claim to intelligent but only claimed to be able to retrieve accurate information and did that well but they are designed to NOT do that.

I remember the early Internet and search engines with advanced boolean search capability like Alta Vista and the early versions of Google before they sold their top search results to the highest bidder.

Then the Internet was mainly academic institutions and community based organizations. The information on the Internet was relatively reliable most of the time. That information is still there if you pay attention to the actual source.

LLMs could use an information base based on actual reliable sources like Encyclopedia Britannica or Wikipedia, or the collections of actual scientific journals or other respected sources.

But instead they have adopted the bigger/more is better approach feeding as much of the Internet as possible into their models, often without permission of the sources/creators. This leads to an information base dominated by misinformation and disinformation leading to results like “there is no water in the Atlantic Ocean”. But obvious errors are not the danger here but the amplification of misinformation and disinformation in the political sphere.

But it is worse. These disinformation models are proving to be even more wasteful of energy and harmful to the planet than the cryptocurrency scam and their believers/followers just as faithful and misguided. And for what. Obviously they hope to make a shitload of money from this scam.

AI is clearly not intelligent, just dangerous.

How Did We Get Here

Let me tell you a story about my early days working for the House of Commons in a non-partisan position serving all Members of Parliament and all Canadians. While we all had our own political opinions, that ranged from right to left, we all worked professionally and in a non- partisan manner to serve the House. And we all got along.

On one particular day we were on what could best be called a self-improvement course. I suppose there was money left in the professional development budget and somebody knew somebody, but that is a different discussion. This course veered into a particular direction that was critical of social programs and public health care suggesting they enabled the lazy. Many of us expressed our opposition to these seemingly American inspired ideas during the seminar. During our first break I was discussing this with a colleague, who happened to be the most right wing member of our staff from conservative Alberta, and I, from NDP stronghold Sudbury, was the most left wing staff member, and we both agreed the seminar was a waste of time and we both decided to go back to our desks and do real work for the rest of the seminar.

The point being that while we had different political outlooks we shared the same Canadian values that all our colleagues did.

There was a time, not really that long ago in the political history of our country, when people on the left respected, and even admired, right wing politicians like John Diefenbaker, Bill Davis, Flora MacDonald and Joe Clark and people on the right felt the same way about politicians like Tommy Douglas, Stanley Knowles and Ed Broadbent. There was a time when we held two Quebec referendums and national debates on Quebec separation in a respectful manner without the level of hatred that is expressed today. This was a time when Canadians had their party preferences but did not fear for their country if their favoured party lost.

I can think of a particular American multi-millionaire and another American billionaire that can share some of the blame for what is happening in Canada today. But the blame also lies with too many of us who have decided to use our ability to control the information we receive to only see what we have already chosen to believe and only listen to those we have chosen to listen to. Unfortunately this leaves too many people in a position to easily fall prey to disinformation and manipulation. But that still does not explain the level of real hatred we see expressed in our political discourse today, particularly against the current Prime Minister for everything from policy decisions to the colour of socks he might choose to wear.

How did we get here.

Postscript

It is blatantly obvious that the vast majority of the political hate (and bigotry) we are seeing today is coming from one end of the political spectrum. It is time for the centre right decide who their values better align with, the far right or the centre, and a time for them to decide who and what they want to be aligned with.

More Liberal Nothingness From Ignatieff

So what are the Liberals' conditions for keeping the government in power. Well actually there are none. The Liberals are not demanding that the government actually do anything, only that it report on what it is doing.

As the CBC reports:

According to Ignatieff, the government must meet the following four conditions to maintain support from the Liberals:

- Provide more details about improving the employment insurance system before the House of Commons votes on budget estimates at the end of the week. The government has said it will introduce unspecified new EI proposals in the fall.

- Give more information about the rate of stimulus spending than included in last Thursday's progress report.

- Show more details on the government's plan to contain the ballooning deficit, instead of offering what Ignatieff called "rosy projections."

- Provide clearer answers on the government's plan to deal with Canada's medical isotopes shortage.

Yessirree, they have to “provide more details”, “give more information”, “show more details” and “provide clearer answers”. However, they are not required to actually do anything.

That's the Liberal hardline. Go Iggy Go.