Artificial Intelligence CXO

Algorithmic Accountability Act: What tech leaders need to know and do now

AI bias, audits and reporting are all key components within the Algorithmic Accountability Act. Find out what what you are promoting can do at present concerning synthetic intelligence and bias.

Capitol Building in Washington DC, USA
Image: Diego Gomez/Adobe Stock

What is the Algorithmic Accountability Act?

“The Act would require all companies utilizing AI to conduct critical impact assessments of the automated systems they use and sell in accordance with regulations set forth by the Federal Trade Commission,” stated Siobhan Hanna, managing director of worldwide AI techniques for TELUS International. “Compelling tech firms to self-audit and report is a first step, but moving towards the implementation of strategies and processes to mitigate bias more proactively will also be key in helping to address discrimination earlier in the AI value chain.”

If the Algorithmic Accountability Act passes, it’s doubtless to set off an auditing of synthetic intelligence techniques on the vendor stage — and additionally inside corporations themselves that use AI of their resolution making.

SEE: Artificial Intelligence Ethics Policy (TechRepublic Premium)

The Algorithmic Accountability Act was reintroduced in April 2022 in each the House and Senate after present process modifications.

“Houses that you never know are for sale, job opportunities that never present themselves and financing that you never become aware of — all due to biased algorithms,” stated Sen. Cory Booker, a invoice sponsor. “This bill requires companies to regularly evaluate their tools for accuracy, fairness, bias and discrimination. It’s a key step toward ensuring more accountability from the entities using software to make decisions that can change lives.”

Are corporations prepared for the problem?

As many as 188 completely different human biases that may affect AI have been recognized. Many of those biases are deeply embedded in our tradition and our information. If AI coaching fashions are primarily based on this information, bias can filter in. While it’s potential that corporations and their AI builders can intentionally embody bias of their algorithms, bias is extra doubtless to develop from information that’s incomplete, skewed or not from a sufficiently various set of knowledge sources.

“The Algorithmic Accountability Act would present the most significant challenges for businesses that have yet to establish any systems or processes to detect and mitigate algorithmic bias,” stated Hanna. “Entities that develop, acquire and utilize AI must be cognizant of the potential for biased decision making and outcomes resulting from its use.”

If the invoice turns into regulation, the FTC would have the authority to conduct AI bias influence evaluation inside two years of passage. Healthcare, banking, housing, employment and training would doubtless be excessive profile targets for examination.

“Specifically, any person, partnership or corporation that is subject to federal jurisdiction and makes more than $50 million per year, possesses or controls personal information on at least one million people or devices, primarily acts as a data broker that buys and sells consumer data, will be subject to assessment,” stated Hanna.

What corporations can do now

Bias is inherent in society, and there may be actually no manner {that a} completely zero bias atmosphere will be achieved. But this doesn’t excuse corporations from making finest efforts to be sure that information and the AI algorithms that function on it are as goal as potential.

Steps corporations can take to facilitate this are:

  • Use various AI groups that usher in many alternative views and views on AI and information.
  • Develop inner methodologies for auditing the AI for bias.
  • Require bias evaluation outcomes from third get together AI system and information distributors that they buy providers from.
  • Place a heavy emphasis on information high quality and preparation of their day by day AI work.


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