The Fintech Times’ Mark Walker recently caught up with Michael Clark, VP global head of digital transformation and futurist at Mastercard Data & Services to discuss data and its relationship with artificial intelligence (AI).
Clark reflected on the oft-quoted analogy of ‘data as the new oil’, noting that the original intent behind this comparison was to highlight the need for data refinement to unlock its true value, rather than simply viewing it as a raw material.
He stressed that data should be regarded as a valuable asset, akin to a utility like water, which has both intrinsic worth and practical applications in our daily lives. He also explained that the rise of AI has helped to elevate the importance of data management, as organisations have realised the need to better understand and utilise their data resources.
Michael Clark, VP global head of digital transformation and futurist at Mastercard Data & Services
The conversation then shifted to the challenges faced by the financial services industry, where the complexity of legacy systems and data silos has hindered the effective deployment of AI. Clark outlined the importance of data quality and the requisite skills to interpret AI-generated insights, underscoring the need for a holistic approach to data management.
Data ownership
The discussion delved into the thorny issue of data ownership, particularly in the context of consumer data and the growing tension between individuals and large technology companies. Clark argued that true data ownership is limited to one’s personal identity, while the data generated through our daily activities is a collaborative asset that requires careful stewardship.
He suggested that AI could play a pivotal role in connecting disparate data sources, providing individuals with a comprehensive view of their health, finances, and other aspects of their lives. This, in turn, could empower consumers to take a more active role in managing their personal data and leveraging it for their own benefit, such as in the prevention and early detection of diseases.
The conversation then turned to the challenges of trust and transparency in AI models, particularly the trend towards private, company-specific language models. Clark acknowledged the merits of this approach, as it allows for greater control over data provenance and model interpretability. However, he also touched on the importance of interoperability and the need to balance individual and societal data interests.
“What AI is giving with us is the ability to connect data for the first time, such as a single view of your health that we’ve never had? So, if we start looking at data as an asset and not something to fear, then actually the word changes in our conversation, because now we can say, well, hang on, what if I had access to all of my data?”
Elevating data
Clark highlighted the importance of elevating data’s role in society, drawing parallels to the essential nature of water. He explained the need to address the decline in critical thinking and data literacy skills, which he attributed to the rapid technological advancements and the tendency to passively accept information presented by digital platforms.
To address these challenges, Clark outlined a three-pronged approach: strengthening existing skills, regaining lost capabilities, and acquiring new competencies. He emphasised the shared responsibility of businesses, governments, and educational institutions in fostering data literacy and critical thinking among both consumers and professionals.
In conclusion, the discussion underscored the pivotal role of data in the age of AI and the urgent need to reframe our understanding and management of this valuable resource. By elevating data as a strategic asset, promoting trust and transparency, and investing in data literacy, Clark argued that organisations and individuals can harness the transformative potential of AI while ensuring its responsible and equitable deployment.
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