Empowering executives to transform their organization and reduce the barriers to adopting emerging technologies.
He ignites the audience’s imagination to forge fresh perspectives on emerging technologies such as Artificial Intelligence (AI). Gerald draws upon his experiences leading strategic projects with interest in storytelling to find new opportunities for organizations to thrive with uncertainty. Beyond the technologies and perspectives, he teaches strategies to foster an innovative culture where the audience returns to work, asking, 'What can we do differently today?'
Gerald O’Connell is a speaker who delivers eye-opening keynotes.
Gerald O'Connell is an accomplished problem-solver and leader with over 30 years of experience in financial services and consulting firms like Aon, GEICO, and PwC.
Part project manager and cultural translator Gerald O’Connell spent the last thirty years specializing in delivering strategic projects in the insurance industry, genetic genealogy, and consulting.
His accomplishments include using data to:
• Build and improve underwriting models,
• improves customer experiences,
• implements new products,
• identifies unknown family members from DNA, and
• identifies financial market anomalies.
He excels at communicating complex subjects to general audiences and executives, delivering complex analyses and compelling visualizations rigorously and creatively.
Gerald has recently been developing low-budget movie projects that bring sci-fi, horror, and fantasy films to worldwide audiences in 2024.
Gerald's Speaking Topics
Are we living in a sci-fi movie? + Artificial Intelligence
Artificial Intelligence (AI) potentially brings significant benefits to our economy and society, such as increased productivity, improved healthcare, and enhanced safety. However, we are faced with the dilemma that this fantastic new technology that brings such exciting benefits also possesses the ability to destroy humanity.
This talk will explore AI from the view of Science Fiction as it has formed our doomsday perspective over the past two centuries but can also identify the solutions to our AI dilemma.
Is AI better than you? + Artificial Intelligence
One of the solutions to the AI dilemma includes imposing strict ethical restrictions on AI development and use. However, we do not set the same rigorous ethical standards for human activity.
This talk will explore historical case studies over theoretical discussions to better understand ethical issues and give a roadmap for applying ethical standards to AI.
Exploring our DNA to find the mysteries of our family + Genetic Genealogy
People exploring their family history will quickly hit roadblocks in the historical records and turn to DNA testing to fill in the gaps. A dilemma exists that distant relatives that hold information do not need to explore family history and, therefore, refrain from engaging with genealogy. Consequently, we turn to DNA analysis to find our DNA connections, only to find other researchers looking for the same information. Therefore, how do we find value in DNA research? This talk will present strategies for using DNA research to understand our family history better.
“We must address, individually and collectively, moral and ethical issues raised by cutting-edge research in artificial intelligence and biotechnology, which will enable significant life extension, designer babies, and memory extraction.”
—Klaus Schwab, The Founder and Executive Chairman of the World Economic Forum
“We’re seeing a kind of a Wild West situation with AI and regulation right now. The scale at which businesses are adopting AI technologies isn’t matched by clear guidelines to regulate algorithms and help researchers avoid the pitfalls of bias in datasets. We need to advocate for a better system of checks and balances to test AI for bias and fairness, and to help businesses determine whether certain use cases are even appropriate for this technology at the moment.”
— Timnit Gebru, research scientist, Google AI
“Harnessing machine learning can be transformational, but for it to be successful, enterprises need leadership from the top. This means understanding that when machine learning changes one part of the business — the product mix, for example — then other parts must also change. This can include everything from marketing and production to supply chain, and even hiring and incentive systems.”
—Erik Brynjolfsson, director of the MIT initiative on the digital economy
“The three big categories [for building ethics into AI] are first, creating an ethical culture; then being transparent; and then finally taking the action of removing exclusion, whether that’s in your data sets or your algorithms.”
—Kathy Baxter, ethical AI practice architect, Salesforce