2020 MMPA Conference: AI and Machine Learning for Complex Business Decision Making
Each year, the Master of Management & Professional Accounting (MMPA) program hosts a one-day MMPA conference on topics that deal with the forces that are shaping our changing landscape in the accounting profession. Given that we are part of the Institute for Management & Innovation (IMI), the MMPA conferences focus on innovations (technological and otherwise) and opportunities afforded by ongoing change. We explore how accountants apply their human skills/values and professional competencies to continually create value.
The MMPA program, which provides a unique combination of the MBA curriculum combined with the CPA pathway, hosts the conference series as part of the student curriculum, inviting academics, members of the accounting profession and practitioners from different disciplines to share their experiences and research to spark new ideas and ways of thinking. We are thankful for our partnerships with CPA Canada and the IMI BIGDataAIHUB (which acts as a sandbox, allowing stakeholders to gather, share idea and learn about big data and artificial intelligence).
MMPA 2020 Conference
Corporations are increasingly relying on big data analytics to develop new strategies such as personalized marketing, predictive inventory management, real-time data monitoring, and cybersecurity protocols. AI and Machine Learning are used to identify business intelligence to assist decision-making in complex social and economic environments. The COVID-19 pandemic has accelerated the digitization of our work environment, with more reliance on technology to make our society more resilient in an increasingly diverse and volatile global economy.
This conference explores applications of AI and Machine Learning in different business and social contexts. We invited a group of world AI experts and industry leaders to share their visions on the social and economic impacts of AI and Machine Learning, and the governance challenges associated with AI technology. Mr. Rahman will discuss his contributions towards developing international standards governing Data & AI applications in the Financial Services sector. Professor Khan will discuss how AI can be used to develop a global early warning system for infectious diseases. Professor Sanders will share her AI expertise in predictive analytics for risk and supply chain management. Ms. Davinder Valeri will highlight CPA Canada’s initiatives on AI applications in future accounting practices. Professor Levi from MIT Sloan School of Management will deliver the keynote speech on using Advanced Analytics in complex business decision-making. Professor Davenport will illustrate how companies can gain competitive advantages in using AI and Advanced Analytics.
Yue Li | Associate Director, MMPA
Thank you for Attending the MMPA 2020 Virtual Conference
Many thanks to all those who attended our 2020 MMPA Conference, “AI and Machine Learning For Complex Business Decision Making”. Our speakers challenged us to think about the role of AI in Accounting, noting that AI is one of many tools in the Accountant’s toolbox (but not the only one).
AI “solutions” can break a budget (or worse) when a more effective lower-tech solution is overlooked, a problem isn’t defined properly, AI is siloed (instead of “systemized”) and data is not well understood.
Repeatedly, we heard that we can’t predict the future with historical data. Powered by human curiosity, creativity, ingenuity we learned that human-augmented AI is the most effective tool to predict pandemics, optimize supply chains, and assist with complex decision making. Accountants have roles to play in AI interpretation, explainability, standards, trust, and ethics, data cleansing, and overcoming “analysis paralysis”.
Accountants’ enduring human capabilities can power the tools of AI and machine learning for complex business decision making as well play an integral role in the data management value chain.
Professor Retsef Levi
J. Spencer Standish (1945) Professor of Operations Management at the MIT Sloan School of Management, Co-Director of the MIT Leaders for Global Operations, MIT. (Read bio)
Partner, Head of Trusted Data & AI Transformation, IBM, Chair, Trusted Data & AI Standards for Financial Services, IEEE. (Read bio)
Professor Kamran Khan
Professor of Medicine and Public Health, University of Toronto, Founder and CEO of BlueDot. (Read bio)
Professor Nada R. Sanders
Distinguished Professor of Supply Chain Management, D’Amore-McKim School of Business, Northeastern University. (Read bio)
CPA, CMA (Read bio)
Professor Thomas Davenport
President's Distinguished Professor of Information Technology & Management, Babson College, co-founder of the International Institute for Analytics. (Read bio)
Keynote and Speakers Agenda
Trusted Data & AI Playbook for Financial Services with Pavel Abdur-Rahman
Artificial Intelligence, Infectious disease, and Resilience from the Pandemic with Professor Kamran Khan
The Humachine: Humankind, Machines and the Future of Enterprise with Professor Nada R. Sanders
Research, Guidance, and Support: CPA Canada with Michael Lionais
Keynote Speech: Designing Intelligent Processes & Systems via Advanced Analytics with Professor Retsef Levi
Competing on Analytics: Business Strategy and AI with Professor Thomas Davenport
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