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Are We Still in Control? How Data and Analytics are Key to Ensuring Your Company’s Narrative

Keys to Data Governance and Accountability

"Who controls the past controls the future; who controls the present controls the past" – George Orwell***

In the classic novel "1984," George Orwell explains that those exerting authority over information can apply influence over the future. There's a suggestion that organizations empowered to shape interpretations can sway memory and understanding. By dictating what data is remembered or erased, these organizations can mold the narrative and shape expectations for the future.

Simultaneously, those in power in the present have the capacity to manipulate or reinterpret anything using data and analytics. This quote underscores the pivotal role of controlling data and leveraging analytics in influencing public perception and consolidating power over time.

All this from a book written in 1949. Who knew that this would be so relevant in today’s data and analytics landscape?

In today's terms, Orwell's quote underscores the power dynamics in controlling information. In our data-driven age, those who control the narrative through data have the ability to influence public perception and shape the course of events. A contemporary example is the recent $368 million fine imposed on TikTok by the European Union. This incident highlights the potential impact of data processing on user privacy, echoing Orwell's warning about controlling the past to dictate the future. TikTok's case serves as a reminder that even platforms with over 1 billion users worldwide must adhere to strict data protection regulations, emphasizing the ongoing challenges in balancing innovation with ethical data practices in our digital landscape.

Companies are struggling with the ability to control their data. I recently attended Qbiz Inc.’s inaugural Executive Data Governance Meetup and found that, regardless of industry, organizations are still having challenges with Data Governance. Whether it’s a taboo word in a company or a lack of priority, organizations are not realizing the value in their Data Governance. But the rise in Artificial Intelligence (AI) has exposed an even greater need for this practice. Gustavo Bermudez and I were examining how organizations currently have the ability to control how their information is being used.

Traditional ways of managing data are no longer effective, where speed and agility are paramount. Balancing speed with regulatory commitments is another matter. Recently, OpenAI learned that its ChatGPT AI chatbot violated GDPR privacy rules and leaked sensitive data. The incident adds to the increasing regulatory scrutiny faced by AI systems globally, with the U.S. Federal Trade Commission and EU regulators investigating similar issues involving multiple technology giants (not to mention the EU AI Act that was passed last December).

I was discussing with Kevin O'Callaghan and he indicated work is needed for transparency on where the data for such models is sourced from. From there asking what   controls are in place to protect people and privacy, beyond what is known in the public domain.  Legal cases and regulation will end up doing the heavy lifting, but ultimately all parties have to control how such data is sourced and whether it is easy or difficult it is for use in large language models (LLMs).  This is something that leans heavily on an organizations ethical control especially with personal data.

So how can we be certain we’re still in control? Governance

The EDM Council discusses the importance of Data Governance in its Cloud Data Management Capabilities (CDMC) Framework. The framework emphasizes the significance of Governance and accountability in effectively managing data in cloud environments, addressing challenges and opportunities associated with scale, standardization, and the shared responsibility model. Key focus areas include defining strategic business cases, extending data ownership roles, and leveraging cloud automation for Data Governance. Key controls in Governance and accountability include:

  • Data Control Compliance – must be monitored for all data assets containing sensitive data via metrics and automated notifications
  • Data Catalog – ownership in a data catalog must be populated for all sensitive data or otherwise reported to a defined workflow
  • Authoritative Data Sources – sources and provisioning points must be populated for all data assets containing sensitive data
  • Data Sovereignty and Cross-Border Movement – sensitive data must be recorded, auditable and controlled according to defined policy

The framework underscores the importance of understanding and implementing controls for managing data sovereignty and cross-border data movement risks.

Meta could have avoided some of its recent issues had it implemented Enterprise Data Governance and robust data controls. By implementing strict data controls, these platforms can more effectively identify and remove inappropriate content through advanced content detection algorithms and reporting mechanisms. Additionally, comprehensive Data Governance frameworks ensure accountability and compliance, enabling companies to respond promptly to legal obligations and regulatory measures, contributing to a safer online environment for everyone. Here are just a couple ways Data Governance could help:

  • Improved Content Moderation Algorithms – Data Governance can facilitate the development and implementation of advanced content moderation algorithms. By leveraging data analytics and machine learning, platforms can more effectively identify and remove inappropriate content.
  • Enhanced Reporting Mechanisms – Establishing clear Data Governance protocols can lead to the creation of standardized and efficient reporting mechanisms for users to flag inappropriate content.
  • Data Sharing and Collaboration – Data Governance frameworks can encourage collaboration and information-sharing between tech companies, law enforcement agencies, and relevant organizations.
  • User Authentication and Age Verification – Strengthening Data Governance around user authentication and age verification processes can help in ensuring that platforms are used by individuals of the appropriate age.
  • Privacy Measures for Victims – Implementing Data Governance policies that prioritize the privacy and protection of victims is essential.
  • Legislation and Regulation Compliance – Data Governance can assist tech companies in complying with evolving legislation and regulations related to safety online. (ReminderRegulation is coming! Listen to what the Senate says at the “Testimony from a Twitter Whistleblower”)
  • Ethical Use of Data – Implementing ethical guidelines within Data Governance frameworks ensures that the use of data aligns with principles that prioritize the well-being of individuals.

These are a few ways current technology can contribute to a safer environment for us all. Issues like the ones discussed above can be avoided.

In this continually evolving technological landscape, where data, technology, and analytics converge, Orwell's words remind us of the need for safeguards, transparency, and ethical considerations. We must all commit to oversight and responsible Data Governance. In a world where data shapes our reality, the imperative is clear: prioritize the ethical use of data to forge a safer and more equitable environment for everyone.

How are you contributing to this crucial conversation, and what steps do you believe individuals and organizations should take to ensure responsible and ethical data practices?

***Original quote also immortalized by Rage Against The Machine in 1999’s Testify

This blog was written by Gregory Hahn who has a new position at Capgemini in charge of data and analytics strategy.

Blog posted by Steven Mintz, aka Ethics Sage, on February 13, 2024. Sign up for Steve's newsletter and learn more about his activities at: https://www.stevenmintzethics.com/.

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