A feminist-inspired multi-stakeholder engagement framework and tools for evolving and enacting social, computational, and legal agreements that govern the lifecycle of an AI system.
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Co-constitution
Addressing friction
Informed refusal
Contestability and complaint
Disclosure-centered mediation
Scenarios (coming soon)
- Gender-Equity
- Healthcare
- Education
- Content Moderation
Learn more about the framework and contact us at: bogdana@mozillafoundation.org
In service of you and a vision for improved transparency and human agency in the interactions between people and algorithmic systems:
- Bogdana Rakova, Mozilla Foundation, Senior Trustworthy AI Fellow
- Megan Ma, Assistant Director, Stanford Center for Legal Informatics
- Renee Shelby, Sociology Department and Legal Studies Program, Georgia Institute of Technology
Graphic design by Yan Li.
With the kind support of Mozilla Foundation.
Informed Refusal
TwSw interventions see refusal as a generative practice - given the opportunity to opt out, individuals are inspired to provide technology companies their critical feedback about what needs to change for them to opt in. The concept of informed refusal comes from Ruha Benjamin’s work where she compares it to the concept of informed consent in medical law, arguing for a justice-oriented approach to constructing more reciprocal relationships between institutions and communities.
We recognize that people hold a multiplicity of dynamic human identities. Inspired by the temporal dynamics in law - writing in the present, reflecting on the past, and encoding the future, we challenge the dominant temporal design of algorithmic systems which have been critically framed as self-fulfilling prophecies and stochastic parrots. We argue for the need to incorporate multifaceted mechanisms to refuse harmful algorithms within the lifecycle of AI including its design, the user interface, as well as contractual agreements such as terms of use and content policies.
We encourage practitioners to ask: What are the assumptions and problem formulations that underpin a particular AI model or system? Who gets to define the default conditions? What does consent mean and what forms does it take? What is the temporal dynamics of consent and its refusal?
Resources:
- Barabas, C., Virza, M., Dinakar, K., Ito, J., & Zittrain, J. (2018, January). Interventions over predictions: Reframing the ethical debate for actuarial risk assessment. In Conference on fairness, accountability and transparency (pp. 62-76). PMLR
- Barabas C (2022) Refusal in data ethics: Re-imagining the code beneath the code of computation in the carceral state. Engaging Science, Technology, and Society 8(2): 35–57.
- Benjamin R (2016) Informed refusal: Toward a justice-based bioethics. Science, Technology, & Human Values 41(6): 967-990
- Benjamin R (2020) Race After Technology: Abolitionist Tools for the New Jim Code. Polity.
- Cifor M, Garcia P, Cowan TL, Rault J, Sutherland T, Chan A, Rode J, Hoffmann AL, Salehi N and Nakamura L (2019) Feminist Data Manifest-No. (Accessed 20 February, 2022)
- Ganesh MI and Moss E (2022) Resistance and refusal to algorithmic harms: Varieties of ‘knowledge projects’. Media International Australia 183(1): 90-106.
- Garcia P, Sutherland T, Salehi N, Cifor M and Singh A (2022) No! Re-imagining data practices through the lens of critical refusal. In Proceedings of the 2022 ACM Conference on Computer-Supported Cooperative Work & Social Computing (pp.1-20).
- Kenway J, François C, Costanza-Chock S, Raji ID and Buolamwini J (2022) Bug bounties for algorithmic harms: Lessons from cybersecurity vulnerability disclosure for algorithmic harms discovery, disclosure, and redress. Algorithmic Justice League. (Accessed 21 February 2023).
- Matias JN, Johnson A, Boesel WE, Keegan B, Friedman J and DeTar C (2015) Reporting, reviewing, and responding to harassment on Twitter. arXiv preprint arXiv:1505.03359
- Shen H, DeVos A, Eslami M and Holstein K (2021) Everyday algorithm auditing: Understanding the power of everyday users in surfacing harmful algorithmic behaviors. In Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2) (pp.1-29).
- Wright S (2018) When dialogue means refusal. Dialogues in Human Geography 8(2): 128-132.
