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Regulating Information Management in the Era of Artificial Intelligence Creation

Numerous threats associated with generative AI encompass various aspects such as privacy violations, security breaches, and ethical quandaries.

Regulating Data Management Amidst the Rise of Artificial Intelligence Generators
Regulating Data Management Amidst the Rise of Artificial Intelligence Generators

Regulating Information Management in the Era of Artificial Intelligence Creation

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In the rapidly evolving world of technology, generative AI has emerged as a top business and technology strategy for 2023. However, its adoption is not without concerns and challenges.

Primary Concerns and Risks

A recent Harris Poll highlights quality and control, safety and security risks, limiting human innovation, and human error due to lack of understanding as primary concerns. Privacy and security concerns are at the forefront, especially for corporate AI use. Cybersecurity, privacy concerns with personal data, and liability are top risks according to KPMG executives.

Training and Education Gap

Despite a 20-fold increase in roles demanding AI skills, only 13% of workers have been offered any AI training by their employers in the last year. This skills gap could potentially hinder the effective and safe implementation of generative AI.

Ethical Concerns

Sixty-four percent of IT leaders surveyed by Salesforce are concerned about the ethics of generative AI. These concerns extend to potential data breaches or liability issues due to the language learning model of a generative AI tool containing sensitive corporate data.

Data Governance and Risk Management

To address these concerns, several companies and startups, such as Flagship Founders and Sealenic, are integrating data governance and risk management strategies into their AI projects. Collaborations with maritime companies like Reederei F. Laeisz, Fairplay Towage Group, and Harren Ship Management are underway to develop and test AI-assisted software.

However, many companies in German-speaking countries are still struggling with AI expertise and strategy implementation, with limited information available about widely established internal AI working groups dedicated to strategy development in data governance and risk management across other companies.

Data Transparency and Quality

Lack of data source transparency and risks from inaccurate or biased data are also significant concerns. Inaccurate or harmful outcomes can occur if data in the model is biased, libelous, or unverified. This has led to lawsuits by artists and writers concerning the use of their works in training models.

Policy and Regulation

Only 26% of IT leaders have no policy in place to govern AI, and only 21% allow AI with no restrictions on the data or applications that employees can use. Forty percent of IT leaders will pursue a multi-pronged approach encompassing storage, data management, and security tools to protect against generative AI risks.

The Role of Cloud Providers

Top cloud providers have released new services to run generative AI projects, lessening the cost, energy usage, and complexity for IT organizations. In 2023, preparing for AI is the leading data storage priority of IT leaders, surpassing cloud migrations from the previous year.

The Future of Generative AI

Major cloud providers and enterprise software vendors are releasing AI-related solutions to meet different use cases and business requirements. With 86% of IT leaders believing generative AI will have a prominent role in their organization soon, it is clear that the challenges and opportunities presented by generative AI are here to stay.

To mitigate risks and ensure the safe and effective use of generative AI, IT and business leaders are encouraged to invest in data governance courses and educate employees on how to properly and safely use AI technologies. This will be crucial in navigating the complex landscape of generative AI and harnessing its potential for innovation and growth.

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