PulseAugur / Brief
EN
LIVE 19:27:02

Brief

last 24h
[3/3] 222 sources

Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. TOOL · Medium — MLOps tag English(EN) ·

    Red Teaming AI Credit Underwriting: How Algorithmic Fairness Frameworks Double as Behavioral…

    This article explores how algorithmic fairness frameworks can be used for red-teaming AI systems in credit underwriting. It suggests that these frameworks, beyond ensuring compliance, can help build more robust and secure machine learning systems for institutional risk management. The focus is on moving towards a defense-in-depth approach for AI in financial applications. AI

    Red Teaming AI Credit Underwriting: How Algorithmic Fairness Frameworks Double as Behavioral…

    IMPACT Enhances AI system robustness and security in financial applications through advanced red-teaming techniques.

  2. RESEARCH · Mastodon — sigmoid.social English(EN) · · [2 sources]

    How can you measure security in # ML systems? Maybe similarly to the way we measure security in software systems. # swsec # appsec BIML wrote about this in a ne

    Berryville IML has released a new report detailing methods for measuring security in machine learning systems, drawing parallels to established software security practices. The report, available for free under a creative commons license, aims to provide actionable insights for applied ML security. AI

    How can you measure security in # ML systems? Maybe similarly to the way we measure security in software systems. # swsec # appsec BIML wrote about this in a ne

    IMPACT Provides a framework for assessing and improving the security posture of machine learning systems.

  3. COMMENTARY · Mastodon — sigmoid.social English(EN) ·

    DWeb Camp looking for proposals on Public AI The call for proposals is open until May 15. The track about Public AI looks interesting. Public AI Strategies for

    The DWeb Camp is seeking proposals for its Public AI track, with submissions due by May 15. This track focuses on strategies for developing LLMs and ML systems that are publicly accessible, accountable, and trustworthy. The goal is to foster AI tools that are collectively governed and serve the common good. AI

    DWeb Camp looking for proposals on Public AI The call for proposals is open until May 15. The track about Public AI looks interesting. Public AI Strategies for

    IMPACT Encourages development of AI systems focused on public good and collective governance.