Artificial Intelligence Bias: On Trust, Complexity, and Diversity

November 7, 2019 | Artificial Intelligence, News
https://dailyalts.com/wp-content/uploads/2019/11/display-dummy-1792512_1920-ai-bias.jpg

Just as in computers “Garbage In = Garbage Out,” so also in Machine Learning: “Bias In = Bias Out.”

Microsoft had to hastily withdraw its Twitter chatbot Tay after it reacted to trolls with racist and misogynist tweets. Presumably, the bot developed this artificial intelligence bias from its machine learning basics.

What is machine learning bias? It’s when an algorithm produces results that are prejudiced due to erroneous assumptions in the machine learning process.

“Algorithms can have built-in biases because they are created by individuals who have conscious or unconscious preferences that may go undiscovered until the algorithms are used, and potentially amplified, publicly” – SearchEnterpriseAI

Artificial Intelligence Bias: the tradeoff

There is an assumption of trust that machine learning data will be input after scanning and verification that it is free of bias.

But what if the bias creeps in due to the sheer complexity of the model, or the number of variables? Bias is, therefore, also possible due to the structure of the algorithm itself. It may become so complex (a “black box”) that humans flounder in their understanding of it.

Melissa Koide, the CEO of FinRegLab, colorfully describes it as “an onion we have to unpeel.”

So, there’s a trade-off here: the power of the algo versus its explainability.

Therefore, human judgment has to be a part of the process, somewhere.

The risks of artificial intelligence bias in financial lending

According to Kenneth Edwards, associate general counsel for regulatory affairs at the lender Upstart, Amazon also faced a bias problem. Automated delivery to ZIP codes with a high African-American population apparently got lower priority.

But what if AI models related to financial lending developed a color bias amongst applications for loans?

It’s cold comfort that traditional human models (unfairly) also suffered bias.

If lending has to be “fair,” how do you get your model to evaluate all the avatars of “fairness?”

There could be hundreds of descriptions of fairness.

One solution could be the introduction of diversity in the humans that control machine learning inputs and as well, create the algorithms.

[Related Story: Auriga Launches WWS AI For Advanced Banking Insights ]

Free Industry News

Subscribe to our free newsletter for updates and news about alternatives investments.

  • This field is for validation purposes and should be left unchanged.


Shape

Latest Alternative Investment News

https://dailyalts.com/wp-content/uploads/2021/07/home-page-section-app.jpg
FinTech: UK-Based BNPL Player Zilch Closes Series B With Additional $110M
July 23, 2021     FinTech, News

The $110 million comprised both debt and equity capital. Zilch, the UK-based BNPL platform has raised an additional $110 million from Goldman Sachs and DMG Ventures. The funding is part…

https://dailyalts.com/wp-content/uploads/2021/07/dollar-2387088_640.jpg
Alternative Investments/Hedge Funds: Inflation Fears Boost Hedge Funds’ AUM To Nearly $4T
July 23, 2021     Alternative Investments, Hedge Funds, News

A market survey by alternatives technology provider Vidrio Financial shows that fears of inflation have helped move substantial fund allocations during the first half of 2021 to alternative assets such…

https://dailyalts.com/wp-content/uploads/2021/07/bitcoin-6251865_640.jpg
Alternative Investments/Digital: Global X Throws Its Hat In The Bitcoin ETF Ring

Global X, the New York-based ETF provider and subsidiary of $560 billion investment manager Mirae Asset, has filed with the SEC for permission to launch a bitcoin ETF titled the…

https://dailyalts.com/wp-content/uploads/2021/07/bitcoin-4011305_640.jpg
Digital Assets: Crypto Adoption Stories From JPMorgan, Gallup Poll, Bitcoin Depot, And UBS
July 23, 2021     Digital Assets, News

Four news bites that show cryptos are hanging on, recent crashes notwithstanding. From bitcoin ATMs to crypto FOMO, here goes….