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 Moments00:00 Introduction01:40 Barriers to Adoption of AI04:09 The Journey to Maturity07:44 Stopping Projects to Prioritise AI09:16 The Design Choices in AI10:22 Ethics and Fairness in AI16:51 Real-time Data Access in Conversational AI19:08 The Impact of AI on Behavior20:40 Ethical Considerations in AI Strategy25:57 Ethics and Fairness in Decision-making26:26 Customer Duty of Care and Fairness30:03 Fairness in AI Decision-Making33:24 Privacy and Legitimate Use of Data34:10 Using Synthetic Data to Fill Data Gaps39:28 Ensuring Fairness in Conversational AI41:14 Addressing Data Gaps for Underserved Communities46:24 Embedded Services for Underserved Communities48:35 The Power of Adjacent Data50:00 Challenges in Productionising Predictive Models51:00 Regulatory and Behavioural Barriers52:23 Importance of Communication and CollaborationFor 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