Machine Learning by doing
Artificial intelligence (AI) is increasingly critical, but manufacturing and air travel in Canada are about putting people first.
Canada invented modern AI that has changed the world, but AI as we know it will simply not be enough to save our industries and the many families they represent. The disruptions of the COVID-19 (coronavirus) and other crises mean things will never be the same.
THIS IS ALSO TRUE OF AI.
Machine Learning by Doing is next-generation AI that puts people first in a special way while improving productivity, profits, fairness and social responsibility. AI that is defined first and foremost by its social impact. In so doing, it generates thought leadership and support for manufacturing and aviation that outperforms the status quo while being socially responsible, multidisciplinary and meeting or exceeding the effectiveness aspirations of stakeholders.
MACHINE LEARNING X DOING IS A unified approach for all stages of the AI research-policy-impact cycle
Identify Research Needs: Working with Canadian advanced manufacturing and aviation stakeholders and their supporters to identify major problems facing their front line organizations for which evidence is scarce and effective action is critical.
Generate Exceptional Evidence: Collecting data directly from organizations and developing 21st Century Responsible AI tools and methods to contribute the most scientific and rigorous credible evidence possible executed with algorithmic fairness and transparency within the organizations.
Facilitate Policy Impact: Machine Learning by Doing integrates capacity building in Canada and durable connections for a more nimble, self-sustaining and robust industrial organization in both manufacturing and aviation as well as public policy.
Kweku Opoku-Agyemang, Ph.D.
Toronto, Ontario, Canada
How I Can Help YOU
what is our social impact?
You may be feeling overwhelmed by ongoing events and struggling to understand your impact in your complex world that can only accept AI that is socially responsible and fair.
This question is more important than ever before. Machine Learning by Doing can help.
HOW CAN we be more effective and responsible?
By giving equal rigor to how computers and people learn in your environment, Machine Learning by Doing can help you understand how to effectively impact the experiences and comfort of your travelers, workers, staff and/or other stakeholders.
IS YOUR BACKGROUND SUITED TO HELping solve my complex problem(S)?
I am uniquely placed to help you with your multidisciplinary problem(s). I have 8 years of post-PhD research expertise in both economics and computer science departments (all at the University of California, Berkeley, often cited as having the best department in economics and in computer science in the world). I am an international research affiliate of the algorithmic fairness working group that externally advises Google and other scientists on Responsible AI research. I have given research presentations on various technical work to the World Bank, Facebook, Members of Parliament from 11 countries and public policy stakeholders such as the former Obama Administration Social and Behavioral Sciences Team. I was invited Chair of a session of the Canadian Economics Association at the University of Calgary.
HOW CAN we arrange a consulting?
Fill out the form, then send an email about your problem to machinelearningxdoing[at]gmail.com.
ML XD 🤖😆 🖥️💪