Exploring the future of AI with Chris Preuss, Principal Data Scientist, Calvin Risk

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Chris Preuss, Principal Data Scientist, Calvin Risk, his thoughts on the future of AI.

As experts in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & and ethical AI deployment?

While the ideation of ethical AI is a shared virtue worldwide, one of the greatest current issues is the gap between theoretical concepts and actualized implementation. Moreover, realizing the potential of responsible AI in enterprise—ultimately a value-adding factor to the firm itself—must be relayed to firms using AI in their workflow, a point not only of regulatory acceptance but of intrinsic benefit to the company’s lifecycle. 

 

How has AI impacted your specific field of expertise, and what transformative changes do you foresee in the near future?

  

Recognizing the immediate need for quantitative AI risk management, lending itself to the aiding of ethical, bias-free models, as well as the strategic functions of Value at Risk and ROI observance of AI portfolios, became a natural thought for the Calvin Risk founding team. From this, we have pioneered this nascent field of AI Risk and Bias Mitigation, adapting and iterating to fit new developments (such as generative AI, the rise of commercial LLM chatbots, and so forth). As the industry matures and AI models permeate firms’ operations, our future prospectus includes the need of AI Insurance becoming a commonplace

 

Ultimately, we look forward to using our conclusive expertise in the sector to push forth responsible AI and its subsidiaries as a whole.

 

 

How do you envision AI shaping various industries, and what advice would you give to businesses seeking to integrate AI into their operations?

  

Our expertise lies in Insurance, Banking, Telecom, High-Tech, and Retail’s AI implementations. The primary innovations underlying the use-cases in these fields involve the instant facilitation of processes, more accurate optimization, and immediate personalization of products—ultimately leading to an increased customer experience and 360-functionalization of firms’ offers. In particular, companies must be open not only to the idea of adoption, but also to the continuous iteration and development of systems once in place coupled with a robust AI Risk Management system, this allows for the most efficient return on one’s AI spend.

 

In your opinion, what opportunities and challenges does AI present for job markets and workforce development worldwide?

Working first-hand in the technical aspects of the AI field provides a unique perspective into the inner workings of AI and its implications for the job market. In general, a common concern of breakthrough technologies is its overtaking of work opportunities, rendering populations left with high unemployment at the cost of machinery. While AI may assume specific aspects of jobs, positions will instead call for practitioners of specialized AI, rather than the completion of the tasks themselves. Rather, people, with their unique skill sets, will shift to managing models and utilizing them to augment daily processes, as is any utilization of technology (very rudimentarily, one must understand the underlying task and sector in order to work with and audit it correctly). In more human-centric activities, AI will instead facilitate the connection and quality of service, being a benefit to humanity rather than a disservice.

 

Can you share an example of an AI application or project that has personally impressed you, and explain why it stands out?

  

One notable project is DeepMind's AlphaFold, which has made significant strides in solving the protein folding problem. This AI system predicts the 3D structure of proteins with remarkable accuracy, a task essential in understanding diseases and drug discovery. The breakthrough achieved by AlphaFold was lauded for potentially accelerating biological research and was a landmark moment in showcasing the real-world impact AI can have on science and healthcare.

 

What measures do you believe should be taken to bridge the AI research gap between developed and developing nations to ensure equitable technological progress?

 

Ultimately, a multilateral approach should be taken to foster the development of AI across various economic regions. Explainable systems will be critical in relaying their use to practitioners in developing nations, especially when implemented in governmental settings. At the same time, a bottom-up approach can ensure equitable progress not only between developed and developing nations, but within developing nations themselves such that AI is readily available to populations interested in using it. Evidently, this addition of AI has the power to uplift economies and accelerate them to a higher degree—whether used in the workplace, educational, or national levels.

 

What 2 people do you admire most in the world of AI in terms of their work?
  

Dr. Yoshua Bengio:

 

Dr. Bengio is a Canadian computer scientist, known for his work on artificial neural networks and deep learning. He's a co-recipient of the 2018 ACM A.M. Turing Award, often regarded as the "Nobel Prize of Computing," along with Geoffrey Hinton and Yann LeCun for their work in deep learning and neural networks which have been fundamental to the advancement of AI.

Dr. Fei-Fei Li:

 

Dr. Li is a Chinese-born American computer scientist, known for her work in computer vision and cognitive neuroscience. She co-founded AI4ALL, a nonprofit dedicated to increasing diversity and inclusion in the field of AI. She has also been a proponent of the development of more human-centered AI technologies.

 

What advice would you give to aspiring AI researchers and enthusiasts who want to make a positive impact in the field?

 

Taking a holistic approach to AI is crucial. With quantitative measures as a key for developers and qualitative for other stakeholders, trustworthy AI can only be achieved through the intersection of these elements. This allows for an all-encompassing, positive impact, with researchers and enthusiasts able to gain a full understanding of the risks and benefits associated with the AI at-use or being studied. Ultimately, careful consideration of risks and their severities are paramount—as AI incidents and severity gradually increase with the increasing applications.

 

If you could solve any global problem in the world with AI, what would it be and why?

 

Curbing the issue of unemployment, on a worldwide scale, as well as the logistical issues that accompany it, has the potential to become a key utilization of AI systems. Though requiring upfront infrastructure costs, AI models can both teach and become a tool for the generation of additional jobs and education levels globally—ultimately providing a higher turnover for countries who readily implement and sponsor its usage across the nation. Moreover, the development of Natural Language Processing (NLP) can be adapted to nearly all languages, communicating in a human-like manner that allows for sovereign adaptation and a plethora of knowledge for all interested.

 

What inspired you to participate in this AI summit as a speaker, and what message do you hope to convey to the audience?

 

With the increasing number of incidents in AI—whether related to technical, ethical, or regulatory risks—we believe a new regard for active, trustworthy AI efforts must be debated on the international level. We look forward to discussing the intricacies of AI governance, model validation efforts, and how risk assessment platforms can not only be an ethical benefit to firms, but also a benefactory one to shareholders.