Consultant, Author and Speaker on the subject of Data and AI Ethics
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about me
A fellow with the London-based Royal Society of Arts and a member of the London Speaker's Bureau, Boinodiris has focused on inclusion in technology since 1999. She is currently the business transformation leader for IBM’s Responsible AI consulting group and serves on the leadership team of IBM’s Academy of Technology. Boinodiris is the author of the book 'AI for the Rest of Us, and is a co-founder of the Future World Alliance, a non-profit dedicated to curating K-12 education in AI ethics. She is pursuing her Ph.D. in AI and Ethics at University College Dublin’s Smart Lab. In 2019, she won the United Nations Woman of Influence in STEM and Inclusivity Award and was recognized by Women in Games International as one of the Top 100 Women in the Games Industry as she began one of the first scholarship programs in the United States for women to pursue degrees in game design and development.
Public Speaker/Master Class Teacher
IBM Consulting's Global Leader for Responsible AI
Co-Founder of the Future World Alliance
The Future World Alliance is dedicated to curating curriculum for AI and Ethics in K-12 education along with passionate members from tech companies around the world.
A subset of my Past Speaker & Teaching Engagements
UAE tech Summit
UAE tech Summit
UAE tech Summit
I presented to the UAE government on the subject of how to have AI better reflect the communities that it serves.
SXSW
UAE tech Summit
UAE tech Summit
I have presented at SXSW on several occasions to cover subjects like Education and the Metaverse
NATO Summit
UAE tech Summit
NATO Summit
I have presented several times to NATO on the subject of serious games and the metaverse
KMWorld
THINK/Interconnect
NATO Summit
I am a big fan of KMWorld and speak there annually. You can catch some of my talks replayed online.
United Nations
THINK/Interconnect
THINK/Interconnect
I presented to United Nations women subgroup on the subject of AI Safety and won an international award for my work volunteering in STEM
THINK/Interconnect
THINK/Interconnect
THINK/Interconnect
I have been Mainstage speakers at both THINK and InterConnect on the subjects of Responsible AI and serious games.
Switchpoint
Switchpoint
Switchpoint
Switchpoint is one of my favorite conferences on the planet. I am a regular speaker of this conference whose focus is Humanitarian design.
Switchpoint
Switchpoint
I serve as an advisor and adjunct professor for NCSU's Executive Education program and on the advisory board for NCSU's Women in tech program
featured on ...
MALCOLM GLADWELL'S SMART TALKS PODCAST : Building Trustworthy AI: A Holistic Approach-- LISTEN NOW
National Public Radio (State of Things): LISTEN NOW
AI, Trust, & Organizational
Culture: LISTEN NOW
Real change, enduring change, happens one step at a time. -- Ruth Bader Ginsberg
BLOGS AND articles
Delivering responsible AI in the healthcare and life sciences industry
As organizations are looking for several ways to utilize and implement Generative AI, this is a very important topic that organizations need to tackle to ensure that the outputs from Generative AI are accurate, trustworthy, explainable, and traceable as it could have significant ramifications for not properly addressing. LINK
HR and Explainable AI: A Human Being in 100,000 Dimensions
Imagine an approach to human resources whereby a human being is perceived in 100,000 dimensions. This new approach would replace the flawed traditional HR systems in place today based on consideration of limited criteria. When a human being gives us consent to use their data, HR organizations can use something called an ontology, a knowledge graph that demonstrates soft skills, hard skills and certifications — with explainable proof. With this approach, we can learn that the computer operator may have a degree in information systems or the customer service agent working two jobs really hadn’t had the time because she was doing her PhD in Physics and would be a great candidate for the quantum field. Today, HR organizations are only looking at people based on very few limited attributes. Now with ontologies, when we can see someone with 100,000 dimensions… we are not trying to find the needles in haystacks because the haystacks are full of needles! LINK
What the Field of Archaeology can teach us about Responsible AI
“Forget everything you think you know about the ancient Minoan culture,” the historian said to me at the palace gates. The story she told me on that hot, dusty day in July has since been pressing on me, like a constant drumbeat -- a reminder of why our work in Responsible AI is so unrestricted in importance by just the demands of the here and now. Let us take you on a journey so that you can understand the very direct correlation between what archaeology can teach us about our high tech field.
Mitigating the risks of Intelligent Automation: Bias, worker displacement and more
Intelligent automation offers much promise to companies to drive efficiencies but it is not the panacea. By adopting a responsible framework for the deployment of such systems, companies can ensure that they are not inadvertently causing individual, societal or indeed economic harm to their business. LINK
How Financial Services Companies Can Become Responsible Stewards of AI
Rapid advances in technology, mobile phone penetration, new players and massive investments in technology are transforming the financial services industry LINK
How the Titanic helped us think about Explainable AI
People are entitled to understand how AI arrived at a conclusion, especially when those conclusions impact decisions about their employability, their credit worthiness, or their potential. Provided explanations need to be easy to understand. LINK
10 Lessons Learned for Assessing and Mitigating Unexpected Patterns in AI Models
You procured or developed an AI model to help your organization. You have heard about the potential for unintended harm if the model output is not tested for bias, so you want to take the responsible steps of auditing the models and then mitigating for any potential harm. Excellent!
Here are some useful steps and best practices for your consideration that we are sharing based on the work we are doing with customers.
Pop Culture, AI and Ethics
Have you opened a new location, redesigned your shop, or added a new product or service? Don't keep it to yourself, let folks know.
Best Practices for Insuring AI Algorithms
Insuring AI could very well be the last brick needed to make true adoption and acceleration of AI across industries a reality. LINK
5 steps to creating a responsible AI Center of Excellence
To practice trustworthy or responsible AI (AI that is truly fair, explainable, accountable, and robust), a number of organizations are creating in-house centers of excellence. These are groups of trustworthy AI stewards from across the business that can understand, anticipate, and mitigate any potential problems. The intent is not to necessarily create subject matter experts but rather a pool of ambassadors who act as point people.
Here, I’ll walk your through a set of best practices for establishing an effective center of excellence in your own organization. Any larger company should have such a function in place.
Getting to Trustworthy AI (VentureBeat)
Artificial intelligence will be key to helping humanity travel to new frontiers and solve problems that today seem insurmountable. It enhances human expertise, makes predictions more accurate, automates decisions and processes, frees humans to focus on higher value work, and improves our overall efficiency.
But public trust in the technology is at a low point, and there is good reason for that. Over the past several years, we’ve seen multiple examples of AI that makes unfair decisions, or that doesn’t give any explanation for its decisions, or that can be hacked. LINK
Pop Culture, AI and Ethics (Forbes)
AI Education Now
The challenge of ensuring that AI is trustworthy is a socio-technological challenge that necessitates a holistic approach. This holistic approach must include a strong focus on PEOPLE and CULTURE that begins with an earnest investment in education. We are not suggesting education for only those higher ed students that self-categorize as future data scientists, machine learning scientists and coders, but education for ALL, starting in K-12.
Comic gallery (subset)
