Category Archives: Deceptions

6 Ways to Improve the Web

6 Ways to Improve the Web

The Web is such an important part of what so many of us do every day.

It helps us find answers to important questions, navigate to places near and far, meet new people, shop, get latest news, weather and stock prices, and discover which of the diminishing, vanishingly small number of of previously-untouched sub-groups Donald Trump has recently trashed.

Still, there is room for improvement. I propose the following 6 ways the Web could become better…

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Blueberries, the Base and the Outside View

Imagine you read a brief news report in a respected peer-review journal such as Nature. The report cites a conclusive study which states that by giving up eating blueberries, you can cut your risk of getting a certain type of normally fatal cancer by 90%. You like blueberries, and eat them fairly regularly.

Would you give up blueberries based on this?

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Killer Blueberries

There are two obvious answers, and, at the risk of just plain speculating, I would suggest each has its typical justification.

A lot of people are going to say “Yes, I’ll give them up: it is not a big sacrifice to make, and if it cuts down the risk of a cancer by 90%, that has got to be good news.”

The No group is going to contain at least some people who are fed up with being told what’s good for them by “the Food Police”, and say “To hell with it, life is too short, I like blueberries, and am going to carry on.” (We saw a lot of this pushback recently in the UK, when the World Health Organization re-classified processed meats as carcinogens, in the same category as smoking, alcohol and asbestos. Although bacon sales went down, there were some people who stubbornly announced they were going to have a damn good fry-up Sunday morning.)

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Superforecasting Will Become the Next Big Thing Unless It Doesn’t

Forecasts That Don’t Mean Much

Comedian George Carlin had a character called Al Sleet, otherwise known as the Hippie-Dippie Weatherman. Sleet’s speciality was vague or ambiguous weather forecasts, and his most famous was:

Tonight’s forecast: Dark. Continued mostly dark tonight, changing to widely scattered light towards morning.

Everyone can find this funny, but it takes a very special kind of intellect like Philip Tetlock to take it seriously. Why seriously? Because Tetlock has spent much of his career studying forecasting, why we get it wrong (as we often do), and whether we can get it right (which, with discipline, we sometimes can).

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A forecast

He has just come out with a new book, Superforecasting: The Art & Science of Prediction, which I am going to discuss in just a second.

But first, we have to talk about dart-throwing chimpanzees.

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Creating Is Not Understanding in AI

Creating and Understanding

The following line was found scrawled on Richard Feynman’s blackboard after he died:

“What I cannot create, I do not understand.”

It would be a fitting gravestone epitaph, coming from someone who was so fanatical about understanding things.

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Feynman’s blackboard at Caltech

Unfortunately, the corollary, “What I can create, I do understand” is not always true. We only need to turn to modern developments in Artificial Intelligence to find an important example of this. Continue reading

Bricks and Mortar in Human-Level Artificial Intelligence

Bricks and Mortar:

Strategic Positioning of a Long-Term, Human-Level AI Project

Bricks and Mortar
Bricks and Mortar

Précis

  • Any 10 year project needs to have a robust strategy for dealing with change during its lifetime
  • This is particularly true for a human-level AI project, as all key aspects of the field are changing dramatically
  • To date, all previous AI projects have been narrowly-focused and highly specialized: designed to achieve one goal (diagnose a disease, play chess, decide when to sell a stock, etc.)
  • Any human-level AI project, by contrast, will be orders of magnitude more complex, integrating sub-systems that will need to work together to achieve many sub-goals simultaneously, so…
  • Any human-level AI project will end up being a cooperative affair, involving many manufacturers/labs producing many specialist components. It is useful to think of these components as bricks, and the larger project as an edifice to be built
  • This heterogeneous nature will lead to novel constructs not seen in previous AI projects. Most notably, a human-level AI project will be a distributed system, not a monolithic program. Some data and third-party AI sub-systems will be called as services, not bolt-on components
  • To carry the “bricks” metaphor to its logical conclusion, a kind of highly dynamic “mortar” will also be required to bind any human-level AI project together: a mechanism that will allow the bricks to discover one another; to coordinate and sequence their activities; to recover gracefully when a component fails, gets upgraded or goes off-line; to communicate with outside sensors, AI services and data
  • The best business strategy involves developing the mortar, not the bricks

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Book Review: What to Think About Machines That Think

Intelligentsia impresario John Brockman has done an admirable job of assembling some very impressive thinkers for his web site Edge.org. Although most are scientists, there is a fair number of people from the other estates, and the cross-fertilisation of ideas frequently draws even hardened specialists out of their shells, to make pronouncements on things well outside their fields of expertise.

Hal and Dave
Hal and Dave

Although this is not always a good thing, it does make entertaining, stimulating discussion, and I can recommend the site wholeheartedly.

Every year Brockman sets a current question to his group (whose members are, cringingly, called “Edgies”), and turns the resulting answers into a book. This year’s question, and the book’s title, is “What do You Think About Machines That Think?”

The responses, which take the form of short essays, are only very roughly organized by theme. These themes bleed slowly from one to another, without dividing section headings. This provides a surprisingly effective minimalist structure to the book, hinting at emergent concepts that transcend the distinct points made by individual authors.

There are so many excellent ideas presented in the book, that I can recommend it, too, without reservation. So rather than write a normal critical review here, I thought it would be more useful to look at these themes, especially how the thinkers have thought through them, rather than just analyse what they’ve written. From this we can glean a lot about the state of the fields of AI and machine intelligence.

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Beethoven’s String Quartet No. 14, Opus 131 I

In 1826, a year before his death, Ludwig van Beethoven completed his string quartet number 14 in C# minor, opus 131.

Although it was not well received by the general public upon its first performance, a rather large number of quite significant musicians seem to have thought highly of it in their time.

Beethoven String Quartet 14, Opus 131, first movement

Beethoven String Quartet 14, Opus 131, first movement

When Schubert first heard the piece, he is reported to have said, “After this, what is left for us to write?” And as he lay dying, a year after Beethoven’s own death, Schubert asked for it to be played, and his closest friends obliged him. It was very possibly the last piece of music Schubert heard in his life.

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Mindfulness Meditation and Detachment I

Mindfulness Meditation and Detachment I

I wonder if there isn’t a certain danger of arriving at a position of emotional and intellectual detachment if one follows the precepts of Mindfulness Meditation as outlined by its founder and chief spokesperson, Jon Kabat-Zinn.

Before saying even a single word more, I’d like to list my qualifications for making such an accusation:

I have none whatsoever.

I have never done a formal Mindfulness programme, have only read one of Kabat-Zinn’s books (the unfortunately-titled Full Catastrophe Living), and of the secondary descriptions and articles I have read – many in scientific journals — pretty much all of them have been very, sometimes wildly, favourable.

Here’s a fact about Mindfulness: It works.

Moreover, if I do have any kind of valid criticism, I am not all that sure I am justified in laying it at the feet of Kabat-Zinn himself, nor his many followers and practitioners. Quite the opposite: I am pretty sure he is not preaching detachment, or at least wouldn’t want to. But as I said in the opening paragraph, I fear that through following the programme, there is a danger of arriving at that position.

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Mindfulness Meditation and Detachment II

In the first part of this essay, I wondered whether the practice of Mindfulness runs the danger of developing into a detached position (a term I shall explain shortly) but then spent the vast majority of the remaining paragraphs describing Mindfulness in very positive terms. I related my own beneficial experience of it. I stated twice: “Mindfulness works.” Finally, I ended with the rhetorical question,

“What’s not to like?”

It is time to answer that question now.

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