What is the future of the development & deployment of AI?

This MeetUp consists of a presentation and a subsequent panel conversation on the development and deployment of AI, comparing the views of hands-on practitioners, managers and business owners. This event co-hosted by Spiced Academy in Berlin, who will provide food & drinks.

Space is limited, and there will be a guest list for non-Spiced Academy students, so please RSVP if you want to come.

The presentation:

M. Murat Ardag, Ph.D, a Data and Scientist Political Psychologist, will present his study utilizing the Stack Overflow 2023 Annual Developer Survey to show the developers' tech stacks, AI tool usage, and their expectations of AI's effects on workflows. The second part of the presentation will explore a causal path model that reveals a cautious attitude to AI by more educated and older developers.

The panel discussion:

During the panel discussion, we will examine the consequences of the findings from business, technical and societal perspectives.

Moderator:

Elizabeth Press, Founder of D3M Labs:

Elizabeth is Founder of D3M Labs, a consultancy, media platform and community dedicated to getting financial value out of data and building cyber secure digital business. Elizabeth has been a Data Leader, Strategy Consultant and Journalist focused on the intersection of technology, business and politics.

Panelists:

M. Murat Ardag, Ph.D., Data Scientist and Political Psychologist:

Murat is a data scientist and political psychologist with 12+ years of experience in academia and 2+ years of experience in the private sector. One of his primary interests is studying the psychological profiles of individuals in data careers and how these differences influence job satisfaction.

*Kseniia Brauer, Founder of mexb.ia:*

With a Master's in Social Science with a focus on Machine Learning, Kseniia has positioned herself at the intersection of technology and social good. As the founder of mexb.ai, she drives the mission to harness AI in addressing mental health needs, ensuring improved well-being and accessibility for our society.

Sam Edds, Lead Data Scientist at Yelp:

Sam is a Lead Data Scientist at Yelp and regularly presents at different conferences on topics such as practical steps to avoid AI disasters, and utilizing computer vision to predict natural disasters. She is an explainable AI advocate and always interested in discussing bias in AI.

Cautious Attitudes of Developers:

• Conservatism vs. Experience: Senior developers might be wary of the hype surrounding AI, preferring tried-and-tested methods. Their experience may make them cautious of potential drawbacks like brittleness (AI's inability to adapt outside its training data).
• Trusting AI Outputs: Transparency and explainability are key. Developers might hesitate to trust outputs they don't understand.

Challenges in AI Development:

• Edge Case Checking: There might be a gap between how thoroughly developers check code for edge cases compared to how rigorously AI models are tested for unexpected inputs.
• Bias in AI: Developers might be more aware of potential biases in their code, whereas AI models can inherit biases from the data they're trained on.

AI for Innovation and Competition:

• Developer Perspective: AI can be a powerful tool for automation, freeing developers' time for more creative tasks. It can also accelerate research and development.
• Company Perspective: AI can lead to faster product development cycles, improved product features, and a data-driven competitive edge.

Priorities: Research vs. Application:

• Groundbreaking Research: These developers might prioritize pushing the boundaries of AI capabilities, focusing on long-term advancements.
• Marketable Applications: Companies need AI solutions that solve immediate problems and deliver a return on investment.

Privacy and Data Security:

• Developer Concerns: They might worry about the ethical implications of AI data collection and usage.
• Company Approaches: Companies might prioritize user privacy while seeking ways to anonymize and secure data for AI development.

Future of AI Technology:

• Areas of Agreement: Both developers and companies likely agree on the transformative potential of AI.
• Areas of Disagreement: The speed and nature of AI integration, as well as potential risks and regulations, could be points of discussion.

Need for Collaboration:

• Open Communication: Clear communication between developers and companies about goals, risks, and expectations is crucial.
• Shared Knowledge: Developers can educate companies on AI capabilities and limitations, while companies can provide insights into real-world application needs.