Responsible, Safe, Ethical, Human-Centered
AI Research & Development
Dr. Scott Allen Cambo h as dedicated his career to helping teams research, design, build, and monitor AI systems that are safe to use, responsibly developed, and trustworthy.
Dr. Scott Allen Cambo h as dedicated his career to helping teams research, design, build, and monitor AI systems that are safe to use, responsibly developed, and trustworthy.
"Today with the release of the Rail License Generator, the goal is to further grow that number by lowering access barriers. The tool was created by the RAIL Working Group — Tooling and Procedural Governance, led by Jesse Josua Benjamin, Scott Cambo and Tim Korjakow"
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"Scott Cambo, who helps run the project, said he expected “a huge increase of cases” involving mischaracterizations of actual people in the future. “Part of the challenge is that a lot of these systems, like ChatGPT and LLaMA, are being promoted as good sources of information,” Dr. Cambo said. “But the underlying technology was not designed to be that."
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“There are also companies [using tech in hiring] that are at best pseudoscientific snake oil and at worst algorithmic phrenology,” said Scott Allen Cambo, a data scientist at tech compliance company Parity AI, which is now called Vera, in the November hearing. “We’ve heard these companies said the audit doesn’t need to be good, it just needs to happen and have been lucky enough to be in a position to turn down these deals. There are of course competitors more than willing to cut corners.”
Read Full ArticleLearn more about approach to helping teams develop responsible, safe, and ethical AI systems.
While I have dabbled in many forms of AI, NLP systems are where I feel most at home.
Primarily with regard to NYC Local Law 144
Being a good steward of sensitive data and the AI that is trained from it is a big responsibility. Check out these resources to learn more.
I have studied with some of the world's top experts in mixed methods research. Learn more about why mixed methods research is critical to understanding and developing good AI systems.
With years of experience in Human-Computer Interaction research and AI development, I have developed a process for building AI systems that are not simply trusted by users, but rather AI that all stakeholders can agree is trustworthy.
Early stages of AI development are often hindered by an inability to distinguish between prototypes, proof-of-concepts, and minimal viable products. By understanding what questions each can answer and how, companies can save the critical time and money needed to see a project through.
A Responsible AI Fellowship led by Xiaochen Zhang: "A diverse group of leading minds committed to shaping AI's future responsibly."
Steering Committee Member & Co-Lead of the Tooling and Procedural Governance Working Group
Helping create a Responsible AI Maturity model to aid organizations in assessing the quality of the responsible AI initiatives and programs.
Member of AI Risk & Vulnerability Alliance (ARVA) working group on developing a taxonomy for the AI Vulnerability Database
Catologing incidents where AI has been observed to cause harm is a critical step toward mitigating that harm.
Aiding the development of the technical programming for the world's premiere conference on Fairness, Accountability, and Transparency in AI systems.
I review for several ACM conferences (FAccT, CHI, CSCW, UIST, DIS, UbiComp) and SAGE Academic Journals like Social Science Computer Review