Quick Summary of Speech from Nicolas Bouzou
AI & Entreprise, Perpignan
Last evening I had the opportunity to join a coterie of technologists, policy-wonks, teachers, and professors at Perpignan, listening to Nicolas Bouzou on his thoughts about how AI is reshaping the world we live, work and play. Nicolas is a leading French economist and essayist, and director of studies in the MBA Law & Management of the University of Paris II Assas.
This is a short English abstract of the talk — much thanks to my friend Pierre Grabalosa who is currently the Dean of Mobile Programming at IMERIR — he was busy rapidly translating (Fr->En)the speech for me. Excuse us if this is not a true reflection of the speech but more of our interpretation of the speech.
Nicolas started the talk by comparing the different growth trajectories of US, China and France (broader Europe) enabled by the rapid progress of technology and creative business model innovations. He used the following three points framework to describe the current state of disparity in AI enabled innovation economy between the USA and China on one side and Europe at the other.
(Access to) Capital: Artificial Intelligence powered businesses demand up-front investments to create, organize and analyze data and EU as a whole is lacking in such bulk investments when compared with China and the USA. While the European have a lot of savings they are no proactive in investing like the people in the USA as there is not much of an incentive to encourage such private investments. Nicolas stressed on the need for a grand, long term plan for the EU that is focused on liquifying assets and capitals to raise the overall levels of investments.
Oligopoly: AI needs a lot of data to create algorithms. Ironically this favors big companies rather than smaller, nimble start-ups. This is one reason why all good news around AI is dominated by FAMGA (Facebook, Apple, Microsoft, Google, Amazon) who have created an overarching business model spanning suppliers and consumers through vertical integration.
Big enterprises have access to huge swaths of proprietary data collected over years that can be used to train machine learning algorithms. Additionally, large enterprises have established a customer base and large enough supplier-distributor ecosystems that are ripe areas for carrying out data-driven experiments. (Note: implementing AI in large companies is harder than you think).
American companies like SpaceX are not just stopping at launching rockets and deploying satellites, they are integrating the entire value chain by building rockets upstream and providing satellite management services to networks downstream. This kind of vertical integration across multiple services (resulting in oligopolies) is seemingly not possible in France due to the existing rules and corporate structures.
Unfaithfulness (or lack of customer loyalty): We as customers are spoiled now with choices and options that we don’t even know existed before. We have less and less reason to be loyal to just one thing. Netflix offers more shows and movies than we can watch realistically in a lifetime, the same can be said about songs streamed on Spotify and about endless aisles of billion items on Alibaba.com. We like choices and we like freshness and these large tech companies are focused on giving us that.
Future of Work & Employment: Nicholas switched gears and spoke about how the new AI-powered economy is not all doom and gloom for humanity but once-in-a-lifetime-opportunity to actually engage in more human work. Robotics and automation will reduce the cost of providing healthcare services that we now hold back due to high investments.
While the AI is good at looking at radiology reports and identifying a tumor, you will still need humans to break the news to the patient (and family) and support the person through therapy sessions to recovery. However, if we just take the current processes and automate them, then we will not get the results we are looking for. This kind of technology will change the process of value creation and distribution and demands a new kind of talent, a different mindset to be successful. To make sense of the AI-powered economy, we must understand the limits of data and algorithms and the role of being humans.
Overall it was an engaging speech and the audience followed up with a good set of questions and follow-on networking over cocktails.
