Pathways to AI Implementation and Excellence: Ethical, Strategic and Operational Insights with Optima and Fenestra

In this episode, the hosts Paul Sweeney (Chief Strategy Officer at Webio) and Dan Blagojevic (Director of Decision Sciences & Machine Learning at Optima) and their guest, Javier Campos (Chief Information Office at Fenestra), discuss the barriers to adoption of artificial intelligence and the importance of maturity assessment in AI implementation.

They explore the need for a clear rule book or recipe book for the journey to maturity and the role of governance in successful AI implementation.

The conversation also looks into the ethical considerations in AI, including fairness and privacy. Paul, Dan and Javier stress the importance of establishing guidelines and principles for ethical AI practices. They discuss the challenges of addressing data gaps for underserved communities and the potential of synthetic data and embedded services to fill those gaps.

The discussion concludes with the power of adjacent data in generating valuable insights. They unpack the challenges and limitations of productionising predictive models, particularly in the context of financial, physical, and mental health. They also consider the regulatory and behavioural barriers that hinder the implementation of predictive models in improving outcomes. The importance of effective communication and collaboration between technical and business teams is a key factor in successful projects.

Takeaways

* Maturity assessment is crucial in AI implementation to identify gaps and set realistic goals.

* Ethical considerations, such as fairness and privacy, should be central to AI strategy.

* Governance and guidelines are essential for ensuring ethical AI practices.

* Synthetic data and embedded services can help address data gaps for underserved communities.

* Adjacent data can provide valuable insights and drive innovation in AI applications.

Key Moments

00:00 Introduction

01:40 Barriers to Adoption of AI

04:09 The Journey to Maturity

07:44 Stopping Projects to Prioritise AI

09:16 The Design Choices in AI

10:22 Ethics and Fairness in AI

16:51 Real-time Data Access in Conversational AI

19:08 The Impact of AI on Behavior

20:40 Ethical Considerations in AI Strategy

25:57 Ethics and Fairness in Decision-making

26:26 Customer Duty of Care and Fairness

30:03 Fairness in AI Decision-Making

33:24 Privacy and Legitimate Use of Data

34:10 Using Synthetic Data to Fill Data Gaps

39:28 Ensuring Fairness in Conversational AI

41:14 Addressing Data Gaps for Underserved Communities

46:24 Embedded Services for Underserved Communities

48:35 The Power of Adjacent Data

50:00 Challenges in Productionising Predictive Models

51:00 Regulatory and Behavioural Barriers

52:23 Importance of Communication and Collaboration

For more:

Webio: https://www.webio.com/

Optima: https://optimapartners.co.uk/

Fenestra: https://www.fenestra.io/

This podcast is produced in partnership with Podlad.com