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Walking the digital tightrope: Implementing AI without compromising privacy

In an era dominated by big data, businesses are increasingly harnessing the power of AI models.

The arrival of ChatGPT late last year shook up the EU's plans to regulate AI
The arrival of ChatGPT late last year shook up the EU's plans to regulate AI - Copyright AFP Karim SAHIB
The arrival of ChatGPT late last year shook up the EU's plans to regulate AI - Copyright AFP Karim SAHIB

The end of January 2024 marked Data Privacy Day. The purpose of Data Privacy Day is to raise awareness and promote privacy and data protection best practices. The theme for 2024 was ‘take control of your data’, reminding global citizens that each of us has rights when it comes to data.

In consideration of the importance of maintaining data privacy, Lakshmikant Gundavarapu, Chief Innovation Officer, Tredence, tells Digital Journal about the importance of incorporating synthetic data and striking a balance between capitalizing on artificial intelligence while safeguarding its use. 

Gundavarapu begins by assessing the various technological changes that have impacted upon businesses during the past year or so: “In an era dominated by big data, businesses are increasingly harnessing the power of AI models such as ChatGPT to revolutionize efficiency and elevate customer service standards.”

Despite the benefits that these technologies offer, Gundavarapu points out that “this surge in AI adoption comes hand in hand with substantial data privacy concerns, particularly prevalent in data-intensive sectors like banking and consumer goods. The pivotal challenge lies in effectively leveraging these advanced AI tools without compromising the confidentiality of sensitive information or violating stringent privacy regulations.”

This means new businesses strategies to embrace these changes, as Gundavarapu points out: “Enterprises must embrace robust data privacy strategies to navigate this complex landscape successfully. This involves meticulous data classification to identify and safeguard sensitive information, minimizing the data input into AI models and implementing advanced techniques like data masking and encryption. Equally essential are stringent access controls and secure data-sharing practices to thwart unauthorized access attempts.”

Some measures are likely to be more effective than others. Drawing on one method, Gundavarapu selects: “A standout solution in this intricate ecosystem is synthetic data. By crafting data that mirrors authentic patterns yet contains no sensitive information, businesses can confidently train and test AI models without risking privacy breaches. This innovative approach presents a dual advantage: It not only fortifies privacy safeguards but also preserves the utility of data for diverse AI applications.”

Ultimately new technology presents a choice. Gundavarapu sees this as: “In essence, businesses must strike a delicate balance—capitalizing on the vast potential of AI while safeguarding data privacy. The incorporation of synthetic data emerges as a prudent step in this direction.”

The choice is most likely going to be towards technology adoption, as Gundavarapu finds: “In our digitally-driven world, responsible AI usage is not just a strategic choice but a technical necessity. It forms the bedrock for upholding customer trust and maintaining industry reputation in an increasingly interconnected and privacy-conscious landscape.”

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Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, business, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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