As with many other vital terms, "Algorithmic Bias" has been politically
appropriated:

https://en.wikipedia.org/wiki/Algorithmic_bias

On Mon, Mar 8, 2021 at 3:18 PM Matt Mahoney <[email protected]> wrote:

> Algorithmic bias, as I learned the term, means the finite subset of models
> that a learning algorithm is capable of learning. For instance, a linear
> regression algorithm, which predicts (x,y) points given x and a training
> set, can only construct models of the form y = mx + b after learning the
> two parameters m and b. There may be other functions that fit the data
> better, but we cannot search all of them, or even all of those with
> description lengths smaller than the training data, because Kolmogorov
> complexity (and therefore AIXI) are not computable. It is impossible to
> have an unbiased algorithm like AIXI.
>
> Ethical AI means one that won't launch an unfriendly singularity. It could
> also mean an algorithm that fails to predict human behavior given their
> ethnic group or gender. We really don't need to worry about the first case
> for a long time. The second case seems unavoidable, and suppressing
> research is likely to perpetuate racism and sexism in humans. Shaming
> researchers and denying that there are differences doesn't make the facts
> go away.
>
> On Mon, Mar 8, 2021, 11:30 AM James Bowery <[email protected]> wrote:
>
>> Here's an example of what I mean by AIXI being valuable in practice:
>>
>> NVIDIA is now coupling their terms of service with the following
>> injunction to AI developers that they avoid "algorithmic bias".
>>
>> Ethical AI
>>> NVIDIA’s platforms and application frameworks enable developers to build
>>> a wide array of AI applications. Consider potential algorithmic bias when
>>> choosing or creating the models being deployed. Work with the model’s
>>> developer to ensure that it meets the requirements for the relevant
>>> industry and use case; that the necessary instruction and documentation are
>>> provided to understand error rates, confidence intervals, and results; and
>>> that the model is being used under the conditions and in the manner
>>> intended.
>>
>>
>> Well well well... just what _exactly_ is "algorithmic bias"?  Huh?  Who
>> decides what is "algorithmic bias"?  How do we prevent bias in the decision
>> of what constitutes "algorithmic bias"?
>>
>> Ockham's Razor as rigorously formalized by the size prior of AIXI's AIT
>> subtheory is useful to sweep away the egregious politicization of the
>> phrase "algorithmic bias".  Note that this practical benefit is an
>> _application_ of the advance in the philosophy of science represented by
>> algorithmic information theory.
>>
>> Until someone comes along and offers as clearly defined (ie: Not "Not
>> even wrong!") philosophy of science, those wielding influence in the field
>> of "algorithmic bias" are being UNETHICAL in failing to advance lossless
>> compression as the most unbiased model selection criterion.
>>
>>
>> On Mon, Mar 8, 2021 at 9:42 AM James Bowery <[email protected]> wrote:
>>
>>> While I agree that the value of a theory is to be found in its
>>> contribution to practice, you are underestimating the value of AIXI in this
>>> regard.  Of course, you are far from alone and there is that old saw
>>> "safety in numbers."
>>>
>>> I simply assumed that the premiere AGI theory, which AIXI _is_, would be
>>> sufficiently familiar to the denizens of an "AGI" group to sustain the use
>>> of acronyms for its two sub-theories.
>>>
>>> On Mon, Mar 8, 2021 at 5:33 AM John Rose <[email protected]>
>>> wrote:
>>>
>>>> So with SDT you were alluding to AIXI Sequential Decision Theory....
>>>> sorry suffering from acronym overload here, need to rewind the Turing tape.
>>>>
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