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The Algorithmic Bias Lab is the research and education division of BABL AI, a consultancy with deep expertise in the ethical production and deployment of artificial intelligence. With the goal of helping organizations build trust with stakeholders and the public in light of growing concerns of the misuse of these technologies, e’ve developed a holistic framework for evaluating/ auditing algorithms based:

  • Fairness
  • Effectiveness
  • Transparency

This lab offers training courses on a variety of topics related to the ethical auditing and evaluation of algorithms. Despite our name, we recognize that bias is only part of the story, and this lab conducts research and outreach to develop and operationalize these principles in a way that gives everyone a voice in how AI should affect our lives.

Courses

Finding your place in AI ethics consulting

This mini-course will outline the most common tasks performed in AI ethics consulting, and give practical advice for finding your place in this quickly growing field.

Algorithms, AI & Machine Learning

This is a technical crash course in Automated Decision (Augmentation) Systems with a focus on bringing non-technical consultants, risk, and policy professionals up to speed on these emerging technologies

Research

The algorithm audit: Scoring the algorithms that score us

In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals …

The algorithm audit: Scoring the algorithms that score us

In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals …

The algorithm audit: Scoring the algorithms that score us

In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals …

Algorithmic Bias and Risk Assessments: Lessons from Practice

In this paper, we distinguish between different sorts of assessments of algorithmic systems, describe our process of assessing such systems for ethical risk, and share some key challenges and lessons for future algorithm assessments and audits. Given the distinctive …

Algorithmic Bias and Risk Assessments: Lessons from Practice

In this paper, we distinguish between different sorts of assessments of algorithmic systems, describe our process of assessing such systems for ethical risk, and share some key challenges and lessons for future algorithm assessments and audits. Given the distinctive …

Algorithmic Bias and Risk Assessments: Lessons from Practice

In this paper, we distinguish between different sorts of assessments of algorithmic systems, describe our process of assessing such systems for ethical risk, and share some key challenges and lessons for future algorithm assessments and audits. Given the distinctive …

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Want to learn more?

Let’s discuss how we can help your organization ensure that your AI and machine learning algorithms are fair and AI governance processes are robust.