[LINK] The Bitter Lesson versus The Garbage Can

[Marghanita da Cruz]

Sadly, not many people learnt the GiGo principle. "In computer science, 
garbage in, garbage out (GIGO)".. 
https://en.wikipedia.org/wiki/Garbage_in,_garbage_out.

Your post reminded me of episode on Big Bang theory episode at 
https://bigbangtrans.wordpress.com/series-6-episode-01-the-date-night-variable/ 
and about Anthropic Principle More about principle at 
https://en.wikipedia.org/wiki/Anthropic_principle

While, I am expounding the virtues of Big Bang Theory 
sitcom("Coincidentally, Robertson had recently read Simon Singh's 2004 
book Big Bang,[55][56] and at the concert he improvised a freestyle rap 
about the origins of the universe.".. 
https://en.wikipedia.org/wiki/The_Big_Bang_Theory).

I was surprised to learn Tom Lehrer only just passed and that was his 
song and not the sitcom's homage to him. '"The Elements" has been 
featured in popular culture many times. ..In The Big Bang Theory "The 
Pants Alternative"'.. https://en.wikipedia.org/wiki/The_Elements_(song)

Of course, Star Trek is a Big part of the series.

Of course visit to Google last week indicated they have an international 
policy on garbage bin colours (or should it be "colors", more on Bins 
"OTTO is a leading waste management solutions company, offering 
comprehensive waste handling related products and services from more 
than 10 production facilities located in 7 countries."... 
https://ottobins.com.au/pages/about-us )

Marghanita

On 7/31/25 19:13, Antony Barry wrote:
> The article "The Bitter Lesson versus The Garbage Can" explores the
> challenge of AI adoption in organizations through two influential ideas:
> the Garbage Can Model from organizational theory and the Bitter Lesson 
> from
> AI research.
>
> - **Garbage Can Model**: Organizations are often much messier and less
> rational than they appear. When teams tried to map out their company’s
> processes, they found confusion, redundancy, and a disconnect between
> official strategy and on-the-ground reality. This model describes
> organizations as chaotic combinations of problems, solutions, and
> decision-makers, making decisions when these elements randomly interact
> rather than through orderly processes[1].
>
> - **The Bitter Lesson (Richard Sutton)**: In AI, attempts to encode human
> expertise into computers (e.g., chess strategies) consistently get
> outperformed by general-purpose AI methods with enough computing power and
> data. Instead of mimicking human reasoning, the best results come from
> letting the AI figure things out itself—even if its methods are opaque to
> human observers[1].
>
> - **Tension in AI Adoption**: Most companies attempt to clarify their 
> messy
> processes before integrating AI, believing automation requires clear 
> rules.
> But the Bitter Lesson suggests the opposite might be true: focus on
> defining good outputs (e.g., a high-quality sales report) and let AI
> navigate the chaos to produce those outputs, potentially finding more
> efficient—if less transparent—paths through organizational mess[1].
>
> - **Human vs. AI Strengths**: Especially for non-profit and mission-driven
> organizations, not all valuable outputs are easily measured. Social
> cohesion, trust, or team morale—outputs that matter deeply—are hard to
> specify and may depend on the very "messiness" AI aims to bypass. 
> There's a
> risk that AI will only optimize what can be measured and neglect aspects
> that require human judgment or emotional intelligence.
>
> - **Fundamental Question**: Will organizations, like chess, eventually
> yield to scalable AI approaches if we provide good output examples? Or are
> they too complex and value-laden for such brute force methods to succeed?
> The article suggests that the answer is not yet clear—companies must
> experiment to discover whether the Bitter Lesson or organizational
> complexity ("the Garbage Can") will prevail[1].
>
> - **Key Takeaway**: The core message is that organizations should
> reconsider whether mapping every process is necessary before AI adoption.
> Instead, defining success clearly and providing sufficient examples for AI
> to learn from may be enough, but human understanding remains crucial for
> complex, value-driven goals. The debate between relying on AI's 
> brute-force
> capability versus respecting the "mess" of human organizations is ongoing,
> and its resolution will shape the future of work.
>
> Sources
> [1] The Bitter Lesson versus The Garbage Can
> https://www.oneusefulthing.org/p/the-bitter-lesson-versus-the-garbage
> [2] The Bitter Lesson versus The Garbage Can
> https://www.oneusefulthing.org/p/the-bitter-lesson-versus-the-garbage?img=https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5afe61f0-bbcf-41c6-9c50-45169ad5d08b_7520x2240.png&open=false
> [3] Comments - The Bitter Lesson versus The Garbage Can
> https://www.oneusefulthing.org/p/the-bitter-lesson-versus-the-garbage/comments
> [4] Comments - The Bitter Lesson versus The Garbage Can
> https://www.oneusefulthing.org/p/the-bitter-lesson-versus-the-garbage/comments?triedRedirect=true
> [5] One Useful Thing | Ethan Mollick | Substack
> https://www.oneusefulthing.org
> [6] Ethan Mollick https://substack.com/@oneusefulthing
> [7] Archive https://www.oneusefulthing.org/archive
> [8] Ethan Mollick's Post
> https://www.linkedin.com/posts/emollick_the-bitter-lesson-versus-the-garbage-can-activity-7355577304275714048-eURS
> [9] This is a great little exploration of AI inside orgs. | Tom ...
> https://www.linkedin.com/posts/tomcritchlow_the-bitter-lesson-versus-the-garbage-can-activity-7355588907901546499-ln34
> [10] The Bitter Lesson versus The Garbage Can
> https://boredreading.com/articles/all/recent/read/152593871/
> [11] The main problem with the “Bitter Lesson” is that there's ...
> https://news.ycombinator.com/item?id=44627888
>
-- 
Marghanita da Cruz
Telephone: 0414-869202
Email:  marghanita at ramin.com.au
Website: http://ramin.com.au