"EFF has been sounding the alarm on algorithmic decision making (ADM) technologies for years. ADMs use data and predefined rules or models to make or support decisions, often with minimal human involvement, and in 2024, the topic has been more active than ever before, with landlords, employers, regulators, and police adopting new tools that have the potential to impact both personal freedom and access to necessities like medicine and housing.

This year, we wrote detailed reports and comments to US and international governments explaining that ADM poses a high risk of harming human rights, especially with regard to issues of fairness and due process. Machine learning algorithms that enable ADM in complex contexts attempt to reproduce the patterns they discern in an existing dataset. If you train it on a biased dataset, such as records of whom the police have arrested or who historically gets approved for health coverage, then you are creating a technology to automate systemic, historical injustice. And because these technologies don’t (and typically can’t) explain their reasoning, challenging their outputs is very difficult."

https://www.eff.org/deeplinks/2024/12/fighting-automated-oppression-2024-review-0

#Algorithms #AlgorithmicDecisionMaking #Automation #PredictiveAI

#Algorithms #AlgorithmicDecisionMaking #Automation: "De Liban, the Legal Aid lawyer, told me that trying to fix the algorithm sometimes distracts from the need to fix the underlying policy problem. Algorithmic decision-making is predisposed to inflict harm if it is introduced to triage support in a benefits system that is chronically underfunded and set up to treat beneficiaries as suspects rather than rights-holders. By contrast, benefits automation is more likely to promote transparency, due process, and “equitable outcomes” if it is rooted in long-term investments to increase benefit levels, simplify enrollment, and improve working conditions for caregivers and caseworkers.

Policymakers should not let hype about generative AI or speculation about its existential risks distract them from the urgent task of addressing the harms of AI systems that are already among us. Failing to heed lessons from AI’s past and present will doom us to repeat the same mistakes."

https://www.lawfaremedia.org/article/the-algorithms-too-few-people-are-talking-about

Scrape and scrutinize is the new rock'n'roll. Whether you despise, don't care, or love #TikTok, today can be the first day of your #dataDonation story in which you become a hero of understanding structure and impact of content curation and affordance of this infamous monolith of #socialMedia! How individual is the #FYP? How is harmful content spread? Is it a lost and found of cultural niches? Let's tackle myths and sing songs of #algorithmicDecisionMaking!

Head to https://dataskop.net/ (App in German)

#dataskop

RT @[email protected]

We heard @[email protected] #GlobalSkills are gearing up for the first Legal TechLab. The lab will explore the implications of emerging computational methodologies on the practice of law through practical hands-on workshops.

#AlgorithmicDecisionMaking #MachineLearning #Python

🐦🔗: https://twitter.com/qubschooloflaw/status/1578349084561526784