May 27, 2022

Recommendations for introducing greater safeguards and transparency into CS conference funding

In Part 1 of this piece, I provided evidence of the extent to which some of the world’s top computer science conferences are financially reliant upon some of the world’s most powerful technology companies. In this second part, I lay out a set of recommendations for ways to help ensure that these entanglements of industry and academia don’t grant companies undue influence over the conditions of knowledge creation and exchange.

To be clear, I am not suggesting that conferences stop accepting money from tech companies, nor am I saying there is no place for Big Tech investment in academic research. I am simply advocating for conference organizers to adopt greater safeguards to increase transparency and mitigate the potential agenda-setting effects associated with companies’ funding of and presence in academic spaces.

While I am not claiming that sponsors have any say over which papers are or aren’t published, in the next few paragraphs I will show how agenda-setting can happen in a much more subtle yet pervasive way.

Resurrecting conferences as “trading zones”

Setting the agenda in a given field means determining and prioritizing topics of focus and investment. Research priorities are not neutral or naturally occurring—they are the result of social and political construction. And because a great deal of CS funding comes from tech companies, these priorities are likely to be shaped by what is considered valuable or profitable to those companies.

An example of the tech industry’s agenda-setting power includes the way in which AI/ML research has been conceptualized in narrower terms to prioritize technical work. For instance, despite its valuable contributions to the understanding of priorities inherent in ML research, the Birhane et. al. paper I cited in Part 1 was rejected from publication at the 2021 NeurIPS Conference with a dismissive meta-review, which is just one example of how the ML community has marginalized critical work and elevated technical work. Other examples of corporate agenda-setting in CS include the aforementioned way in which tech companies’ definitions of privacy and security vary from those of consumer advocates, and the way in which the field of human-computer interaction (HCI) often focuses on influencing user behavior rather than stepping back to reflect on necessary systemic changes at the platform level.

In deciding which conferences to fund, and shaping which ideas and work get elevated within those conferences, tech companies contribute to the creation of a prestige hierarchy. This, in turn, influences which kinds of people who self-select into submitting their work to and attending those conferences. Further, the sponsorship perks afford companies a prominent presence at CS conferences through expos and other events. Combined, these factors mold CS conferences into sites of commercially oriented activity.

It is important to make space at top conferences for work that doesn’t necessarily advance commercial innovation. Beyond simply serving as a channel for publishing and broadcasting academic papers, conferences have the potential to serve as sites of critique, activism and advocacy. These seemingly secondary functions of academic gatherings are, in actuality, critical functions that need to be preserved.

In “Engaging, Designing and Making Digital Systems,” Janet Vertesi et al. describe spaces of collaboration between scholarship and design as “trading zones”, where engagements can be corporate, critical, inventive, or focused on inquiry. While corporate work engages from within companies, critical engagement requires the existence of a trading zone in which domain scientists, computer scientists and engineers can meet and engage in dialogue. Vertesi et al. write, “Critical engagements typically embrace intersections between IT research and corporations yet eschew immediate pay-offs for companies or designers.”

Even if sponsoring companies don’t have a direct hand in deciding which work gets published, their presence at academic conferences gives them both insight into ideas and work being shared among attendees, and opportunities to push specific messaging around their brand through advertising and recruitment events. Therefore, instituting sponsorship policies and increasing transparency would help to both curb their potential influence, as well as make clear to conference participants the terms of companies’ financial contributions.

Introducing greater safeguards around conference sponsorship would not be unprecedented; for example, there have been similar efforts in the medical community to curb the influence of pharmaceutical and medical device manufacturing companies on clinical conferences.

Asking accountability conferences to practice what they preach

In particular, tech conferences whose mission is explicitly related to ethics and accountability deserve a higher level of scrutiny for their donor relationships. However, my survey of some of the most prominent conferences in this space found that many of them do not provide a list of donors, nor do they disclose any sponsorship policies on their websites.

That said, some conferences have been reevaluating their fundraising practices after recognizing that certain sponsors’ actions were not aligning with their values. For example, in March 2021, the ACM Conference for Fairness, Accountability, and Transparency (FAccT) suspended its sponsorship relationship with Google in protest of the company’s firing of two of its top Ethical AI researchers, who had been examining biases built into the company’s AI systems.

FAccT committee member Suresh Venkatasubramanian tweeted that the decision to drop Google as a supporter was “in the best interests of the community” while the committee revised its sponsorship policy. Conference sponsorship co-chair Michael Ekstrand told VentureBeat that having Google as a sponsor could impede FAccT’s Strategic Plan. (It should be noted that FAccT still accepted funding from DeepMind, a subsidiary of Google’s parent company Alphabet, for its 2021 conference.)

The conference recently published a new sponsorship policy, acknowledging that “outside contributions raise serious concerns about the independence of the conference and the legitimacy that the conference may confer on sponsors and supporters.” Other conferences, like the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO) and the Association for Computational Linguistics (ACL) Conference have also posted sponsorship and/or conflict of interest policies on their websites.

While it might be expected that ethics and fairness-oriented conferences would have a more robust protocol around which funds they accept, it is in the best interest of all CS conferences to think critically about and mitigate the constraints associated with accepting corporate sponsorship. 

Recommendation of Best Practices

In many instances, accepting corporate sponsorship is a necessary evil that enables valuable work to be done and allows greater access to resources and opportunities like conferences. In the long term, there should be a concerted effort to resurrect computer science conferences as a neutral territory for academic exploration based on what scholars, not corporations, deem to be worthy of pursuit. However, a more immediate solution could be to establish and enforce a series of best practices to ensure greater academic integrity of conferences that do rely on corporate sponsorship. 

Many scholars, like those who signed the Funding Matters petition in 2018, have argued in favor of establishing rigorous criteria and guidelines for corporate sponsorship of research conferences. I have developed a set of recommendations for conferences to serve as a jumping-off point for ensuring greater transparency and accountability in their decision-making process: 

  • Evaluate sponsors through the lens of your organization’s mission and values. Determine which lines you’re not willing to cross.
    • Are there companies whose objectives or outputs run counter to your values? Are there actions you refuse to legitimize or companies whose reputation might significantly compromise the integrity of the conferences they fund? Review your existing sponsors to ensure that none of them are crossing that line, and use it as a threshold for determining whether to accept funding from others in the future.
    • For example, in the sponsorship policy for the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), organizers reserve the right to “decline or return any funding should the sponsorship committee decide that the funding source is misaligned with the mission of the initiative and conference.”
  • Be transparent about who is sponsoring your conference, how much they are contributing, and what benefits they receive as a condition of their contributions.
    • While many conferences do list the logos of their sponsors on their websites, it is not often clear how much money those organizations gave and how exactly it was used. To ensure greater transparency, publish a list of sponsors on your website and in other promotional materials and make the details of your call for sponsorship publicly available and easily accessible. 
    • Make sure to make this information public ahead of the conference, so that invited speakers and other attendees can make an informed decision about whether or not they want to participate. (1)
  • Develop rigorous policies to prevent sponsors from influencing the content or speakers of conference events. 
    • Establish a solid gift acceptance policy and thorough gift agreement outlining the kinds of funding you will and will not accept to ensure that your donors’ support is not restricted and does not come with strings attached.
    • For example, the FAccT conference recently published a new statement outlining their practices around sponsorship and financial support, which denies sponsors say over any part of the conference organization or content. In addition, sponsors can only contribute to a general fund, rather than being able to specify how their contributions are used.
  • Encourage open discussion during the conference about the implications of accepting corporate funding and potential alternatives.
    • For example, the ACM Conference on Computer Science and Law has committed to devoting time to a “discussion of practical strategies for and ethical implications of different funding models for both research and conference sponsorship in the nascent ACM Computer Science and Law community.”
  • Make sure the industry in general, or any one company in particular, is not over-represented among sponsors or conference organizers
    • Consider whether certain sponsors might be working to whitewash or silence certain areas of research. What are the interests or intentions of the organization offering you sponsorship funds? What do they hope to gain from this relationship? (2)
    • For example, the EEAMO sponsorship committee commits to “seek[ing] funding from a diverse set of sources which may include academic institutions, charitable organizations, foundations, industry, and government sources.”
  • Consider seeking alternative, industry-independent sources of funding whose interests are less likely to conflict with the subject/mission of your conference.
    • That being said, it is important to bear in mind that, as Phan et al. pointed out in their recent paper, “philanthropic foundation funding from outside Big Tech interests present different and complex considerations for researchers as producers and suppliers of ethics work.” This is why having a diversity of sources is preferable.

In working to reclaim conferences as a space of academic exploration untainted by corporate interests, the field of computer science can help to ensure that their research is better positioned to serve the best interests of the public.

(1) Several speakers backed out of their scheduled appearances at the UCLA Institute for Technology, Law & Policy’s November 2021 Power and Accountability in Tech conference after learning the center had accepted sponsorship money from the Koch Foundation, which has funded attacks on antiracist scholarship.

(2) For example, in 2016, the Computer, Privacy, & Data Protection Conference (CPDP) chose to stop accepting sponsorship funding from Palantir after participants like Aral Balkan pulled out of a panel and described CPDP’s acceptance of the company’s contributions as “privacy-washing”.

Many thanks, once again, to Prof. Arvind Narayanan for his guidance and support.

The tech industry controls CS conference funding. What are the dangers?

Research about the influence of computing technologies, such as artificial intelligence (AI), on society relies heavily upon the financial support of the very companies that produce those technologies. Corporations like Google, Microsoft, and IBM spend millions of dollars each year to sponsor labs, professorships, PhD programs, and conferences in fields like computer science (CS) and AI ethics at some of the world’s top institutions. Industry is the main consumer of academic CS research, and 84% of CS professors receive at least some industry funding. All of these factors contribute to the significant influence tech firms wield over the kinds of questions that are and aren’t asked about their products, and which information is and isn’t made available about their social impact. 

As consciousness about these conflicts of interest builds, we are seeing growing calls from scholars in and around CS to disentangle the discipline from Big Tech’s corporate agenda. However, given the extent to which much of CS academia relies on funding from major tech corporations, this is much easier said than done. As I argue below, a more achievable yet valuable goal might be to introduce better safeguards in spaces like conferences to mitigate undue corporate influence over essential research.

I will make my case in two parts. First, in today’s post, I will:

  • Provide a quick overview of discourse regarding Big Tech’s dominance in CS research, and
  • Use a dataset I’ve compiled to illustrate the extent to which conferences—an essential arena for knowledge sharing in the field of computer science—are financially reliant upon some of the world’s most powerful technology companies.

In my second post, I will follow up with my recommendations for steps that can be taken to minimize the potential chilling or agenda-setting effects brought on by corporate funding on CS research.

A short survey of concerns about Big Tech’s influence

Relying on large companies and the resources they control can create significant limitations for the kinds of CS research that are proposed, funded and published. The tech industry plays a large hand in deciding what is and isn’t worthy of examination, or how issues are framed. For instance, a tech company might have a very different definition of privacy from that which is used by consumer rights advocates. But if the company is determining the parameters for the kinds of research it wishes to sponsor, it can choose to fund proposals that align with or uphold its own interpretation. 

The scope of what is reasonable to study is therefore shaped by what is of value to tech companies. There is little incentive for these corporations to fund academic research about issues that they consider more marginal or which don’t relate to their priorities. 

A 2020 study on artificial intelligence research found that “with respect to AI, firms have increased corporate research significantly,” in the form of both company-level publications as well as collaborations with elite universities. This trend was illustrated in an analysis by Birhane et al. of top-cited papers published at premier machine learning conferences, which revealed “substantive and increasing corporate presence” in that research. In 2018-19, nearly 80% of the annotated papers had some sort of corporate ties, by either author affiliation or funding. Moreover, the analysis found that corporate presence is more pronounced in the conference papers that end up receiving the most citations.

Birhane et al. write, “the top stated values of ML… such as performance, generalization, and efficiency may not only enable and facilitate the realization of Big Tech’s objectives, but also suppress values such as beneficence, justice, and inclusion.”

One of the most vocal critics of Big Tech’s “capture” of CS academia is Meredith Whittaker, a former Google employee-turned Senior Advisor on AI at the Federal Trade Commission. She argues that tech companies, hoping to muffle critics and fend off mounting regulatory pressure, are eager to shape the narrative around their technologies’ social impact by funding favorable research. This has led to widespread corporate sponsorship of labs, faculty positions, graduate programs, and conferences—all of which are reliant on these companies for not only funding, but often also access to data and computing resources. This industry capture of tech research—wherein corporations are strategically funding research or public campaigns in a way that serves their own agenda—has been described by scholars like Thao Phan et al. as “philanthrocapitalism.”

Furthermore, as Whittaker argues, the tech industry’s dominance in CS research “threatens to deprive frontline communities, policymakers, and the public of vital knowledge about the costs and consequences of AI and the industry responsible for it—right at the time that this work is most needed.” Recognizing this threat, other ex-Googlers like Timnit Gebru and Alex Hanna have taken the initiative to launch the Distributed AI Research Institute, in an effort to create space for “independent, community-rooted AI research free from Big Tech’s pervasive influence.”

I do wish to make clear that receiving funding from an organization that doesn’t completely align with one’s values does not necessarily mean one’s research is compromised. Corporate funding of AI research is not inherently bad, and academics who do not accept Big Tech money can still produce ethically questionable research. Furthermore, individuals who accept Big Tech funding can still be critical of the corporations’ products and their influence on society. 

However, I agree with academics like Moshe Y. Vardi who argue that we must grapple with the contradictions inherent in accepting funding for research such as AI ethics from companies whose interests may run counter to the public good. In a recent article, Vardi, who is the senior editor of Communications of the ACM(1), urged his colleagues to think more critically about their field’s relationship to “surveillance-capitalism corporations”, writing: “The biggest problem that computing faces today is not that AI technology is unethical—though machine bias is a serious issue—but that AI technology is used by large and powerful corporations to support a business model that is, arguably, unethical.” 

Analysis: FAAMG companies dominate conference sponsorship

One way to begin to address these conflicts of interest is by reflecting on the conditions of knowledge creation and exchange—in spaces such as academic conferences—and thinking critically and openly about the compromises and tradeoffs inherent in accepting funding from the industry that controls the subject of one’s study. In the field of computer science, conferences are the primary venue for sharing one’s research with others in the discipline. Therefore, sponsoring these gatherings gives firms valuable influence over and insight into what’s happening at the cutting edge of topics like machine learning and human-computer interaction.

In an effort to get a better understanding of who the major players are in this realm, I reviewed the websites for the top 25 CS conferences (based on H-5 index and impact score) to compile information about all of the organizations that have financially supported them between 2019 and 2021. I found that a majority of the most frequent and most generous sponsors, often donating tens of thousands of dollars per conference, were powerful technology companies.

This spreadsheet contains sponsorship data for the top 25 most frequent sponsors (2). Of the 10 sponsors who supported the largest numbers of different conferences in the past three years, five are “FAAMG” companies (Facebook, Apple, Amazon, Microsoft, Google)—six if you count DeepMind, a subsidiary of Google’s parent company Alphabet. No non-profit organizations, government science funding agencies, or sponsors from outside the U.S. or China appeared among the top 10.

Overall, among the most frequent and most generous supporters of the top 25 CS conferences, the only non-tech/non-corporate donor was the National Science Foundation, which sponsored five different conferences (11 total gatherings) with donations typically ranging between $15,000 and $25,000. 

In addition to having their company name and logo listed on conference promotional materials, top sponsors (who often give upwards of $50,000) receive perks such as opportunities to sponsor prizes or students grants, complimentary registrations and private meeting rooms, access to databases of conference registrants interested in recruitment opportunities, virtual booths or priority exhibition spaces, advertising opportunities and press support, and access to attendee metrics on “exhibitor dashboards”. A “Hero Sponsor” who gave $50,000 or more to the 2021 Conference on Human Factors in Computing Systems (CHI), for example, would have received 34 different benefits – which cumulatively create opportunities for continuous access to and influence on attendees throughout the event.

It is difficult to get an accurate estimate of exactly how much money each company donates to these conferences, as these numbers are not consistently reported to the public. Some conferences only publish a list of supporters with no details about how much each one gave. Others assign sponsorship levels such as “Platinum” or “Diamond”, but the monetary value associated with each level varies by conference and year. When dollar amounts are provided, they often represent a potential range of several thousand dollars—for instance, a Platinum Sponsor of the 2021 SIGMOD/PODS conference might have given anywhere between $16,000 and $31,999. Furthermore, it is difficult gain insight into how exactly these funds are used.

Given the extent of financial entanglement between Big Tech and academia, it might be unrealistic to expect CS scholars to completely resist accepting any industry funding—instead, it may be more practicable to make a concerted effort to establish higher standards for and greater transparency regarding sponsorship.

In Part 2 of this article, I will recommend steps that can be taken to minimize the potential chilling or agenda-setting effects brought on by corporate funding on CS research.

(1) Six of the top 25 CS conferences in the world are organized by ACM, the Association for Computing Machinery. Between 2019 and 2021, many of those conferences were largely funded by American tech companies like Apple, Amazon, Facebook, Google, IBM, and Microsoft, and Chinese ones like Alibaba, Baidu, ByteDance, and Huawei.

(2)  I have compiled a conference sponsorship database that includes extensive data that is not included in this spreadsheet. If you are interested in reviewing it, or in collaborating on further data collection, I would be happy to share it privately.

Many, many thanks to Prof. Arvind Narayanan and Karen Rouse for their thoughtful guidance on and support with this piece.