FEATURED PAPER
By Paul Grignon
SKEMA Business School
Lille, France
ABSTRACT
Artificial Intelligence is exponentially empowering our decision support systems and many beneficial transformative applications are yet to come. However, concerns of disruptive use of AI have recently called our attention on major issues of responsibility, liability and transparency. This report surveys the landscape of risk assessment in contract management with AI and highlights 10 primary attributes of measure in order to identify best alternatives with the purpose to better forecast, prevent and mitigate these threats and maximize AI benefits. We analyze but do not conclusively resolve the issue of unpredictability. We focus instead on the criteria to build on and advocate for robust and ethically responsible AI contract management, recognizing the qualities of inconveniences so as to build great beneficial leading projects.
To this effect, we support 4 recommendations:
- Transparency in decision making
- Core ethical values
- Responsibility for mistakes
- Mitigating social/global dislocation
Key words: Artificial Intelligence, Ethic Management/governance, Responsible AI practices, Responsible research and innovation, Risk Assessment, Risk Management
INTRODUCTION
Last June 26, 2018, on Capitol Hill in Washington D.C., the Subcommittee on Research and Technology and Subcommittee on Energy Hearing on Artificial Intelligence opened with the statement “With Great Power Comes Great Responsibility”![1]
Since the first program[2] especially engineered to mimic the problem-solving skills of a human being by RAND corporation scientists in the 1950’s, the development of Artificial Intelligence has been exponential in all industries. AI is now becoming an essential part of our lives and economy and has the potential to make our lives better in many ways. Algorithms are playing an increasingly large role and the capabilities and beneficial impacts at all levels are innumerable, from keeping spam out of your inbox or deciding what books or holiday destination to buy online to diagnosing and treating cancer. Artificial intelligence can also help us manage highly complex systems such as for instance the system at the heart of the Port of Los Angeles container terminal or similarly, monitor the share market for suspicious trading activity or assist with ground and air traffic control worldwide. In other words, as AI shapes our lives, it also links our future closely to its own in all fields – Education, Commerce, Energy, Agriculture, Space Travel, Transportation, Healthcare and many others.
AI projects and programs cover a wide size and complexity range of undertakings and large-scale assets…
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Editor’s note: This paper was prepared for the course “International Contract Management” facilitated by Dr Paul D. Giammalvo of PT Mitratata Citragraha, Jakarta, Indonesia as an Adjunct Professor under contract to SKEMA Business School for the program Master of Science in Project and Programme Management and Business Development. http://www.skema.edu/programmes/masters-of-science. For more information on this global program (Lille and Paris in France; Belo Horizonte in Brazil), contact Dr Paul Gardiner, Global Programme Director paul.gardiner@skema.edu.
How to cite this paper: Grignon, P. (2019). Artificial Intelligence: Committing to achieving the next frontier, PM World Journal, Vol. VIII, Issue VI, July. Available online at https://pmworldlibrary.net/wp-content/uploads/2019/07/pmwj83-Jul2019-Grignon-artificial-intelligence-committing-to-next-frontier.pdf
About the Author
Paul Grignon
Lille, France
Paul Grignon is a Centrale Lille Engineering final year currently on a Double MSc in Data Science and Global Project and Programme Management & Business Development at SKEMA Business School under the direct supervision of Dr Paul D Giammalvo, Senior Technical Advisor, PT Mitrata Citragraha and Professor Paul Gardiner, Program Director & DBA Scientific Director.
With his solid Data Science major and continuous interest for the latest technologies and developments, he has built up robust technical knowledge and proficiency in computation methods & tools and techniques, notably machine learning, goal driven design, modelling, statistics & probabilities and data analysis. Meanwhile his passion for challenging AI projects & programmes and diverse hands-on experiences alongside dedicated R&D experts have been valuable opportunities to collaborate closely with scientific community, business leaders and management on complex Machine Learning and deep Learning projects, further sharpening his keen sense of collaborative work and commitment to long-term, responsible data science projects.
His international background and current PMI/CAPM/PMP®, APMG/PRINCE2 competency development course combined to his fast learning-by-doing and multi-tasking capabilities testify to his multi-dimensional appreciation of high-performance Data Decision Science and his positive attitude towards the strategic challenges of complex projects and programs. His ambition is to collaborate on ambitious projects that meet the challenges at every stage in the process.
Paul speaks fluent English, Spanish and French and basic Japanese.
Paul can be contacted at p.grignon33@gmail.com
[1] Subcommittee on Research and Technology and Subcommittee on Energy Hearing – Artificial Intelligence. (2018, June 26). Retrieved from https://science.house.gov/legislation/hearings/subcommittee-research-and-technology-and-subcommittee-energy-hearing-artificial
[2] History of Computers and Computing – The Logic Theorist. (n.d.). Retrieved from https://history-computer.com/ModernComputer/Software/LogicTheorist.html
