Alphabet, Inc. – Algorithm Disclosure (2022)

Outcome: Pending

Whereas, legislators, regulators, academics, and civil society increasingly require information to help understand how algorithmic systems can lead to discriminatory and other harmful outcomes in education, labor, medicine, criminal justice, and online platforms. (1) 

Bipartisan lawmakers have introduced the Filter Bubble Transparency Act, which would require companies to provide a version of their products which uses an “input-transparent” algorithm. (2) The Social Media Disclosure and Transparency of Advertisements Act introduced in Congress would force disclosure regarding online targeted advertisements. (3) In December 2021, Washington, D.C. Attorney General Karl Racine introduced the Stop Discrimination by Algorithms Act, which would require companies to audit algorithms for discriminatory impact. (4) General artificial intelligence bills or resolutions were introduced in at least 17 U.S. states in 2021, and enacted in four. (5) 

The European Union’s proposed Digital Services Act will require online platforms “to maintain and provide access to ad repositories, allowing researchers, civil society and authorities to inspect how ads were displayed and how they were targeted,” and will require auditing, disclosure, and transparency of “recommender systems.” (6) 

In 2020, Black content creators launched litigation against YouTube and Alphabet for allegedly violating laws intended to prevent racial discrimination. (7) In 2021, an investigation by The Markup found that Google Ads “blocks advertisers from using 83.9 percent of social and racial justice terms”. (8) White supremacist and anti-Muslim ideologies have appeared on YouTube and can lead to offline violence; for example, the New Zealand Royal Commission found that content on YouTube radicalized the man who massacred 51 people at Christchurch mosques in 2019. (9) 

In 2020, Google fired Timnit Gebru, co-lead of Google’s AI ethics team, after she conducted research that found Google’s technology could perpetuate racism and sexism. (10) 

Promoting fairness, accountability, and transparency in artificial intelligence is central to its utility and safety to society. The Open Technology Institute has recommended a set of algorithmic disclosures for tech companies. (11) Deloitte has said algorithmic risk management “requires continuous monitoring of algorithms”. (12) The Mozilla Foundation and researchers at New York University have put forward recommendations and technical standards for algorithm and ad transparency. (13) 

Resolved: Shareholders request Alphabet go above and beyond its existing disclosures and provide more quantitative and qualitative information on its algorithmic systems. Exact disclosures are within management’s discretion, but suggestions include, how Alphabet uses algorithmic systems to target and deliver ads, error rates, and the impact these systems had on user speech and experiences. Management also has the discretion to consider using the recommendations and technical standards for algorithm and ad transparency put forward by the Mozilla Foundation and researchers at New York University.

(1) https://d1y8sb8igg2f8e.cloudfront.net/documents/Cracking_Open_the_Black_Box.pdf 

(2) https://finance.yahoo.com/news/bipartisan-bill-seeks-curb-recommendation-225203490.html 

(3) https://trahan.house.gov/news/documentsingle.aspx?DocumentID=2112 

(4) https://oag.dc.gov/release/ag-racine-introduces-legislation-stop 

(5) https://www.ncsl.org/research/telecommunications-and-information-technology/2020-legislation-related-to-artificial-intelligence.aspx 

(6) https://ec.europa.eu/commission/presscorner/detail/en/QANDA_20_2348 

(7) https://www.hollywoodreporter.com/business/business-news/youtube-alleged-racially-profile-artificial-intelligence-algorithms-1298926/ 

(8) https://themarkup.org/google-the-giant/2021/04/09/how-we-discovered-googles-social-justice-blocklist-for-youtube-ad-placements 

(9) https://www.cnbc.com/2020/12/08/youtube-radicalized-christchurch-shooter-new-zealand-report-finds.html 

(10) https://www.wired.com/story/google-timnit-gebru-ai-what-really-happened/ 

(11) https://www.newamerica.org/oti/reports/why-am-i-seeing-this/promoting-fairness-accountability-and-transparency-around-algorithmic-recommendation-practices/ 

(12) https://www2.deloitte.com/content/dam/Deloitte/us/Documents/risk/us-risk-algorithmic-machine-learning-risk-management.pdf 

(13) https://blog.mozilla.org/en/mozilla/facebook-and-google-this-is-what-an-effective-ad-archive-api-looks-like/

https://foundation.mozilla.org/en/campaigns/mandating-tools-to-scrutinize-social-media-companies/

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3898214

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