Algorithms, AI & Machine Learning

Putting the AI in AI ethics

What you’ll learn

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. The goal is to gain a sufficient understanding of modern techniques to perform risk analysis and governance.

This is part of a larger series of courses by The Algorithmic Bias Lab, the research and education division of BABL AI. The lab conducts research and training in algorithmic auditing and the responsible production and governance of artificial intelligence. You can find sample lectures from previous training sessions on our Youtube channel.

What you’ll learn

People working on the ethics and governance of AI and emerging technologies, or those looking to transition into the field

People that need to interface between technical teams and executives or senior management

People who lack a deep technical background in algorithms, AI, and machine learning

Develop a roadmap for acquiring expertise that can lead to the ability to bring value to clients and humanity in the field of AI Ethics and Governance

People that feel like a deeper understanding of these technologies is needed to further their career

What can you do after taking this course?

  • List and understand the most common techniques used in AI and machine learning
  • Understand the methods, data, and resources needed to create machine learning and statistical models for automated decision systems (ADMs)
  • Identify critical value judgments that must be made in the development of ADMs
  • Communicate effectively and confidently with development teams and executive decision makers
  • Use Python to create basic algorithms without fear

What will you be doing?

  • 30 lectures (asynchronous)
  • 4 synchronous Q&A sessions with the instructor
  • 26 short quizzes
  • 4 coding projects (in Python)
  • 10-15 hours of effort per week for approximately 12 weeks
  • Dedicated Slack workspace for student collaboration/networking
  • Certificate of completion is provided with 70% or greater score

This course is part of a 5-course certification program for AI and Algorithm Auditors. Anyone can take the course and get a certification.

About the Instructor

Shea Brown is the founder and CEO of BABL AI, a research consultancy that focuses on the ethical use and development of artificial intelligence. His research addresses algorithm auditing and bias in machine learning, and he serves as a ForHumanity Fellow that sets standards for the organizational governance of artificial intelligence.

He has a PhD in Astrophysics from the University of Minnesota and is currently an Associate Professor of Instruction in the Department of Physics & Astronomy at the University of Iowa, where he has been recognized for his teaching excellence from the College of Liberal Arts & Sciences.

Curriculum

1: Introduction & Overview

Welcome to the course! (13:12)

The state of algorithmic risk (8:36)

Demarcating the sociotechnical system (8:59)

Course Resources

2: Conceptual Overview

General taxonomy (14:28)

Methods (22:03)

Model - Inference - Learning paradigm

Intelligent Agents (17:34)

Written Exercise #1

3: Classic Algorithms

Data Structures (26:21)

Basic Statements (15:46)

Functions (10:17)

Don’t just take our word for it

Here’s what our graduates have to say…
Thanks to the rigorous program at BABL AI, I am now equipped with the expertise to consult companies and governments on responsible AI. I can guide organizations in building AI products that prioritize fairness, transparency, and explainability.

Additionally, I can assist in sourcing AI products that adhere to responsible AI principles, educate customers about the risks associated with generative and discriminative AI, develop responsible AI governance capabilities, and collaborate with governments to implement responsible AI initiatives. My journey with BABL AI has been a remarkable one.

– Abhinav

Throughout the course, I gleaned a framework for the science, laws and critical thinking behind AI auditing. Dr. Shea Brown and his team provided an excellent balance of theoretical knowledge and practical applications so that I could feel confident in working with a team to identify, analyze and test risks of the systems all around us… BABL AI created a welcoming environment for people regardless of professional background. I felt confident in scaling my knowledge and skills without a science background and also in my lived experience being respected as part of the auditing process.

– Luna

I have done many training programs in the field of AI Ethics and AI Assessments and/or Audits and I can say that the AI and Algorithm Auditor Certificate Program from BABL AI is definitely one of the best on the market. Prof. Shea Brown does an excellent job both as Instructor and Mentor. Shea and the BABL AI team were always kind and helpful. We did a cohort based training as the first movers, I must admit that the cohort was amazing and made the training a great journey but it is also suitable for individuals who can do it on their own, adjusting their pace with their other responsibilities.

– Mert

What I particularly appreciated about this program was its ability to strengthen my understanding in areas where my knowledge was previously relatively limited. The content was not only thoroughly well-balanced, covering both foundational and advanced topics, but also very engaging and interesting. The unique nature of the program really stood out; despite my extensive search for similar courses, none matched the depth and relevance in risk management offered here.

-Tony HibbertAI Governance Expert, ING Bank

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Algorithms, AI & Machine Learning

Putting the AI in AI ethics

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