Notice of Exempt Solicitation

Pursuant to Rule 14a-103

Name of the Registrant: Alphabet, Inc.

Name of person relying on exemption: Trillium Asset Management, LLC

Address of person relying on exemption: Two Financial Center, 60 South Street, Suite 1100, Boston, MA 02111

The attached written materials are submitted pursuant to Rule 14a-6(g) (1) promulgated under the Securities Exchange Act of 1934.

 

     
 

 

 

 

May 5, 2022

 

Shareholder Proposal Regarding Algorithm Disclosure

Submitted at Alphabet, Inc.

 

At the Alphabet, Inc. Annual Meeting on June 1, 2022, please vote FOR Proposal 15 requesting that the company provide more quantitative and qualitative information on its algorithmic systems.

 

Shareholder Proposal 15 states:

 

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.

 

In 1999, law professor Lawrence Lessig coined the phrase “code is law” as a useful shorthand to remind us that the choices of computer system designers have a profound ability to shape our society.1 The prescience of his phrase is quite obvious to us now as we regularly see the multitude of ways that decision makers at tech companies can influence so much of our personal, professional, and civic lives.

 

But, while we already know how important it is to understand that “code is law” we are only at the beginning of understanding its implications in a world where the code being written is for algorithmic systems, artificial intelligence, and machine learning that are exponentially more powerful than the pop-up ads of the 1990s.

 

Given the power of these systems, it is deeply concerning to realize how little we know about them and what their impacts are. This “black box” quality of Alphabet’s algorithmic systems, artificial intelligence, and machine learning makes it extremely difficult for investors to evaluate how well the company is managing the regulatory risk it faces from proposed laws like Filter Bubble Transparency Act, The Social Media Disclosure and Transparency of Advertisements Act, Stop Discrimination by Algorithms Act, and Digital Services Act.2

 

It also makes it harder for investors to evaluate how well the company will avoid controversies like the one Alphabet did not avoid in 2021 when an investigation by The Markup found that Google Ads “blocks advertisers from using 83.9 percent of social and racial justice terms”3

 

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1 https://www.harvardmagazine.com/2000/01/code-is-law-html

2 https://finance.yahoo.com/news/bipartisan-bill-seeks-curb-recommendation-225203490.html; https://trahan.house.gov/news/documentsingle.aspx?DocumentID=2112; and https://ec.europa.eu/commission/presscorner/detail/en/QANDA_20_2348

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

 

     
 

 

 

 

And as a report by Deloitte concluded “Increasing complexity, lack of transparency around algorithm design, inappropriate use of algorithms, and weak governance are specific reasons why algorithms are subject to such risks as biases, errors, and malicious acts.”4

 

In our proposal we point out that regulators in the US and the EU, civil society organization, and academics are not only asking for more transparency, but are proposing guidelines for how to do that. Given this guidance from organizations like The Mozilla Foundation and researchers at New York University, we believe there is a high quality roadmap for tech companies and investors to follow.5

 

It is clear that Alphabet has ongoing challenges to managing its artificial intelligence research groups which call into question the integrity of its work in this area. For example, on May 2, 2022 the New York Times reported that “Less than two years after Google dismissed two researchers who criticized the biases built into artificial intelligence systems, the company has fired a researcher who questioned a paper it published on the abilities of a specialized type of artificial intelligence used in making computer chips.”6 These continuing controversies strongly suggest that greater transparency is called for.

 

Finally, the company argues in its opposition statement that it has sufficient disclosures and that the proposal should not be supported because it would require “[p]roviding proprietary information”. On the first point, we believe that the existing disclosures are inadequate as evidenced by the regulatory risks, ongoing controversies, and the requests from civil society organizations. With respect to “[p]roviding proprietary information”, the company appears to be selectively ignoring the language in the proposal that “[e]xact disclosures are within management’s discretion.” In no way, do we seek information that would create the problems that the company raises and accordingly have been sure to provide these protections. But it is also important to note that the guidance from organizations like The Mozilla Foundation and researchers at New York University do not require proprietary information be disclosed.

 

For these reasons we are urging Alphabet shareholders to vote for Proposal 15.

 

IMPORTANT NOTICE: The views expressed are those of the authors as of the date referenced and are subject to change at any time based on market or other conditions. These views are not intended to be a forecast of future events or a guarantee of future results. These views may not be relied upon as investment advice. The information provided in this material should not be considered a recommendation to buy or sell any of the securities mentioned. It should not be assumed that investments in such securities have been or will be profitable. To the extent specific securities are mentioned, they have been selected by the authors on an objective basis to illustrate views expressed in the commentary and do not represent all of the securities purchased, sold or recommended for advisory clients. The information contained herein has been prepared from sources believed reliable but is not guaranteed by us as to its timeliness or accuracy, and is not a complete summary or statement of all available data. This piece is for informational purposes and should not be construed as a research report.

 

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

5 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

6 https://www.nytimes.com/2022/05/02/technology/google-fires-ai-researchers.html

 

     
 

 

 

 

This is NOT a solicitation of authority to vote your proxy. Please DO NOT send us your proxy card as it will not be accepted.

 

 

 

 

 

 

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