Predicting the future of work presents significant challenges due to the intricate interplay between technological advancements and human decision-making. To better understand the potential outcomes and critical decision points, more sophisticated models are necessary.
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Decision Making in Uncertain Times
With (Australian) Robodebt and the (UK) Post Office in the news, now is a great time to reconsider how we govern our organisations and institutions. How is it that highly regarded executives and boards went so far astray?
Continue readingThe limits of generative AI
Whilst cruising the interwebs I can across a nice description of the limits of large language (LLMs) models.
Continue readingDistributed stupidity
There’s been a recent up tic in interest in the ethics of AI, and the challenge of AI alignment. Particularly given the challenges at OpenAI, the consequences of which are still appearing the news. Many pundits think that we’re on the cusp of creating an artificial general intelligence (AGI), or that AGI is already here. There’s talk of the need for regulations, or even an “AI pause”, so that we can get this disruptive technology under control. Or, at least, prevent the extinction of humanity.
AGI is certainly a good foundation for building visions of dystopian futures (or utopian future, if you choose), though we do appear to reading a lot into the technology’s potential. Tools such as large language models (LLMs) are powerful tools and definitely surprising (for many) but (as we’ve written before) they don’t appear to be the existential threat many assume.
Continue readingSchool Life in 2024 A.D.
An interesting bit of paleofuture has been appearing in several social media feeds (on reddit, for example). I’ve converted it to text (below) for ease of reading.
Continue readingContinue readingEven the effects already discovered are due to chance and experiment rather than to the sciences; for our present sciences are nothing more than peculiar arrangements of matters already discovered, and not methods for discovery or plans for new operations.
Aphorism VIII. Francis Bacon, Novum Organum, Book 1, 1620
Where will LLMs take us?
Not a week seems to pass by without some surprising news concerning large-language models (LLMs). Most recently it was when an LLM trained for other purposes played chess at a reasonable level. This seemingly constant stream of surprising news has led to talk that LLMs are the next general-purpose technology—a technology that affects an entire economy—and will usher in new era of rapid productivity growth. They might even accelerate global economic growth by an order of magnitude, as the Industrial Revolution did, providing us with a Fifth Industrial Revolution.
Continue reading“I am still struggling to find a proper definition of AGI… ur thoughts”
The short answer is that AGI is a bit meaningless as a term as we don’t really know what ‘I’ is. The best approach is the assume that AGI means “human-like intelligence in machines” while accepting that “human-like intelligence” is something of an unknown.
Continue readingThe coming wave
This book describes itself as the work of ‘the ultimate insider’. This seems rather apt as it provides us with a glimpse of what the technocratic chattering class are saying about the current AI moment. Unfortunately it doesn’t provide us with insight into how this current moment will play out as the view from inside appears to be is quite poor, lacking the perspective need to really grapple with this question.
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The trust deficit between workers and organizations isn’t personal. It’s systemic.
In uncertain times, leaders should embrace ambiguity and adopt an “act to decide” approach, taking small, exploratory actions to navigate unpredictability. This method prevents premature commitments based on incomplete data and fosters adaptability. By tolerating uncertainty and leveraging interconnected ecosystems, organizations can thrive.
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