Failure is an Option

jaron lanier 2014[su_quote]For three decades, the AI world was trying to create an ideal, little, crystalline algorithm that could take two dictionaries for two languages and turn out translations between them. Intellectually, this had its origins particularly around MIT and Stanford. Back in the 50s, because of Chomsky’s work, there had been a notion of a very compact and elegant core to language. It wasn’t a bad hypothesis, it was a legitimate, perfectly reasonable hypothesis to test. But over time, the hypothesis failed because nobody could do it. ~ Jaron Lanier[/su_quote]

[su_dropcap style=”simple”]M[/su_dropcap]any writers use a metaphor of the type “theory T has failed to explain phenomenon P” or “the field of F has failed…”

For example:

The modern materialist approach to life has conspicuously failed to explain such central mind-related features of our world as consciousness, intentionality, meaning, and value. [1]

Ever since the Crash of 2008 there has been a widespread recognition, both among economists and the general public, that economic theory has failed. [2]

The enterprise of achieving it artificially—the field of ‘artificial general intelligence’ or AGI—has made no progress whatever during the entire six decades of its existence. [3]

…Where Artificial Intelligence Went Wrong…At the beginning of AI, people were extremely optimistic about the field’s progress, but it hasn’t turned out that way. [4]

Why Symbolic AI Failed: The Commonsense Knowledge Problem [5]

What Is Wrong With These Metaphors?

The authors invariable jump straight into the philosophical and/or scientific and/or technical reasons why T or F might be wrong, and why their alternative way may be correct.

However, it is not necessarily true that a theory is wrong merely because it hasn’t produced a particular result. In fact, it can’t produce a result. It doesn’t produce anything. “Producing” and “failing” are things that people do. Using the metaphor on a theory or framework shifts the blame onto inanimate abstractions.

This can obscure the true reason as to the so-called failure. Science typically requires experiments, and experiments often require technology. Just developing the technology for a single project could require vast amounts of money and time and people. And then the theory might be wrong or need to be updated and you spend a bunch more resources on the tech.

Projects are notoriously ridden with failure just by their nature. It doesn’t even matter what the project is about.

The Theory vs. the Project

My point is that a theory may be correct, yet not have been proven or involved in a successful implementation simply because of project management and funding.

This can go on indefinitely…it all depends on the organizational contexts which produce the interest in a theory, the management of projects, and funding for those projects.

Likewise, project shenanigans could make a wrong theory seem correct by veiling it with project-related implementation successes.


Rocket Science

Imagine if the US hadn’t spent spent $136 billion on the Apollo Project leading up to the 1969 moon landing. With less money, it might never have been finished, at least not as early. In this alternate history, someone might have declared in 1970 that the field of rocket science had failed to get us to the moon and therefore we needed a new discipline.

It’s perfectly fine to try starting an alternative discipline. But it is notnecessarily true that a theoretical framework has failed to do anything if management and funding has prevented exhaustive experimentation and successful implementation cycles.

Projects Fail All the Time

Around the world, millions of projects are failing right now. Some of them may be successful by certain metrics, such as generating revenue or generating publications, but unsuccessful in terms of implementing full examples of a theoretical framework. Some might be doomed from the start as a result of bad planning. Some may be death march projects.

If the project is confused with the theoretical framework, people might avoid the framework for decades fearing that it was the cause of failure when in fact the cause was pathological project management.


[1] Description of Thomas Nagel, Mind and Cosmos: Why the Materialist Neo-Darwinian Conception of Nature Is Almost Certainly False

[2] George Soros, “Remarks at the Festival of Economics”

[3] David Deutsch, “Creative blocks”

[4] Yarden Katz, “Noam Chomsky on Where Artificial Intelligence Went Wrong”

[5] Notes on a lecture by Hubert Dreyfus


  • Samuel H. Kenyon is an amateur AI researcher, software engineer, interaction designer, actor, and writer. He blogs at where this post previously appeared. Republished under creative commons license.