{"id":43788,"date":"2023-06-08T07:00:12","date_gmt":"2023-06-08T11:00:12","guid":{"rendered":"https:\/\/centricconsulting.com\/?p=43788"},"modified":"2024-03-08T08:44:35","modified_gmt":"2024-03-08T13:44:35","slug":"ai-adoption-how-to-navigate-and-establish-ai-governance-security-and-ethics","status":"publish","type":"post","link":"https:\/\/centricconsulting.com\/blog\/ai-adoption-how-to-navigate-and-establish-ai-governance-security-and-ethics\/","title":{"rendered":"AI Adoption: How to Navigate and Establish AI Governance, Security and Ethics"},"content":{"rendered":"

As we wrap up our series about using AI in the workplace, we discuss the importance of AI governance, security and ethics. We provide recommendations for defining policies and guidelines, setting up decision-making processes, securing AI solutions and data, and addressing ethical considerations while promoting responsible and effective AI adoption within your company.<\/h2>\n
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In our previous blog post<\/a>, we discussed the importance of preparing your workforce for the AI revolution. Today, as we wrap up our series, we will delve into a crucial aspect of AI adoption: AI governance, security and ethics.<\/p>\n

As businesses increasingly embrace AI technologies, they must navigate a complex landscape of regulatory, security and ethical concerns to ensure a successful AI and digital transformation.<\/p>\n

Keeping abreast of cybersecurity threats is an ongoing effort that has intensified the work of cybersecurity professionals. When exploring ChatGPT and other tools, we should advocate for appropriate AI governance to ensure that people use ChatGPT in an ethical and responsible way that aligns with the organization\u2019s values and goals.<\/p>\n

Mira Murati, chief technology officer of OpenAI and co-creator of ChatGPT and other AI models, has voiced her support in the need of regulations to address AI security and ethical concerns. Sam Altman, OpenAI\u2019s chief executive officer, echoed these concerns<\/a> when he testified before congress recently, telling the Senate Judiciary subcommittee that, \u201cregulatory intervention by governments will be critical to mitigate the risks of increasingly powerful models.\u201d<\/strong><\/p>\n

ChatGPT\u2019s viral moment highlights how this tool caught everyone by surprise with its abilities. As AI tools evolve and are adopted, the need for governance and regulations becomes more important. While waiting for regulations, we encourage our clients to adopt internal AI governance.<\/p>\n

It\u2019s important to note that I wrote this from the perspective of businesses using AI tools versus businesses creating AI tools.<\/p>\n

The Importance of AI Governance<\/h2>\n

AI governance is crucial for organizations using AI in the workplace<\/a>, as it helps promote responsible and ethical AI usage, ensures compliance with laws and regulations, manages risks, maintains consistency and standardization, supports skill development, fosters trust and transparency, and aligns AI adoption with long-term strategic goals.<\/p>\n

Our recommendation is that organizations rally and rapidly adopt a governance structure to manage AI adoption by following these steps:<\/p>\n

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  1. Establish a cross-functional AI governance committee:<\/strong>\n
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    1. Identify key stakeholders:<\/strong> Determine the key stakeholders from IT, legal, human resources and various business units who have the relevant expertise and interest in AI governance.<\/li>\n
    2. Define roles and responsibilities:<\/strong> Clearly outline the roles and responsibilities of each committee member to ensure efficient decision making and collaboration.<\/li>\n
    3. Set regular meetings:<\/strong> Schedule periodic meetings to review AI projects, discuss concerns and make decisions related to AI governance.<\/li>\n
    4. Encourage continuous learning:<\/strong> Promote ongoing learning among committee members to stay updated on the latest AI tools, usage and best practices.<\/li>\n<\/ol>\n<\/li>\n
    5. Define AI policies, guidelines and best practices:<\/strong>\n
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      1. Conduct a thorough review:<\/strong> Analyze existing AI tools and technologies within your organization to understand the current state of AI use.<\/li>\n
      2. Research industry standards:<\/strong> Investigate AI governance practices and recommendations from industry experts, regulatory bodies and peers to inform your organization’s policies.<\/li>\n
      3. Develop tailored policies and guidelines:<\/strong> Create a comprehensive set of AI policies, guidelines and best practices that align with your organization’s values, goals and industry requirements.<\/li>\n
      4. Communicate and train:<\/strong> Ensure all relevant employees are aware of the AI policies, guidelines and best practices through training sessions, workshops, and internal communications.<\/li>\n<\/ol>\n<\/li>\n
      5. Set up a clear decision-making process for AI implementation and use:<\/strong>\n
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        1. Define AI tool approval criteria:<\/strong> Establish criteria for evaluating and approving AI tools, considering factors such as business impact, cost, risk and ethical implications.<\/li>\n
        2. Create a prioritization framework:<\/strong> Develop a framework for prioritizing AI investments based on factors like strategic alignment, expected ROI and data leakage risk.<\/li>\n
        3. Establish project oversight:<\/strong> Set up a team to monitor implementation and rollout to ensure the company properly implements and follows its governance plan.<\/li>\n<\/ol>\n<\/li>\n
        4. Ensure regular audits and assessments of AI tool usage:<\/strong>\n
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          1. Develop an AI audit and assessment plan:<\/strong> Create a plan that outlines the scope, frequency and methodology for auditing and assessing AI tool usage.<\/li>\n
          2. Assign audit responsibilities:<\/strong> Designate individuals or teams responsible for conducting AI audits and assessments, ensuring they have the necessary expertise and objectivity.<\/li>\n
          3. Monitor AI performance:<\/strong> Continuously monitor the performance of AI tools against predefined goals, KPIs and ethical standards.<\/li>\n
          4. Identify and address risks and issues:<\/strong> During audits and assessments, identify potential risks and issues related to AI tools and develop action plans to address them.<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

            Securing AI Solutions and Data in the Workplace<\/h2>\n

            As AI tools become an integral part of the workplace, ensuring the security of AI solutions and data security is crucial<\/a> to mitigate risks, protect sensitive information and maintain compliance. This focus on AI security is necessary because the improper usage of AI tools can lead to unintended data breaches, regulatory violations and reputational damage.<\/strong><\/p>\n

            Leaky Data: The Risks of Accidental Proprietary Information Exposure<\/h3>\n

            One of executives\u2019 primary concerns is \u201cleaky data,\u201d or the accidental release of proprietary information to a third-party system without appropriate legal agreements, protections and controls in place.<\/p>\n

            Samsung Semiconductor allowed its engineers to access ChatGPT<\/a>. Over the course of 20 days, Samsung recorded multiple uses of ChatGPT that included the transmission of proprietary and confidential data. This accidental exposure is a critical risk that worries security and compliance personnel.<\/p>\n

            Key steps to securing AI systems and data while using AI tools include:<\/h4>\n
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            1. User Education and Awareness:<\/strong>\n
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              1. Train employees on secure AI tool usage, including guidelines for handling sensitive data and recognizing potential security threats.<\/li>\n
              2. Encourage a security-conscious culture where employees understand the importance of protecting AI systems and data.<\/li>\n<\/ol>\n<\/li>\n
              3. Implementing Robust Access Controls:<\/strong>\n
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                1. Limit access to AI tools and data to authorized personnel with appropriate privileges.<\/li>\n
                2. Use multi-factor authentication to further enhance the security of AI systems.<\/li>\n<\/ol>\n<\/li>\n
                3. Monitoring and Auditing AI Tool Usage:<\/strong>\n
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                  1. Regularly monitor and log employee use of AI tools to detect potential misuse or unusual behavior.<\/li>\n
                  2. Conduct periodic audits of AI tool usage to ensure compliance with security policies and best practices.<\/li>\n<\/ol>\n<\/li>\n
                  3. Data Protection:<\/strong>\n
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                    1. Implement data classification policies to identify sensitive data and apply appropriate security measures.<\/li>\n
                    2. Encrypt sensitive data, both in transit and at rest to safeguard it from unauthorized access.<\/li>\n<\/ol>\n<\/li>\n
                    3. Incident Response Planning:<\/strong>\n
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                      1. Develop and maintain an incident response plan to address security incidents related to AI tool usage.<\/li>\n
                      2. Regularly test and update the plan to ensure its effectiveness and adaptability to evolving security threats.<\/li>\n<\/ol>\n<\/li>\n
                      3. Collaborating with External Security Experts:<\/strong>\n
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                        1. Engage with external security experts to stay informed about the latest AI security trends and best practices.<\/li>\n
                        2. Seek guidance on implementing advanced security measures for AI tools, as needed.<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                          By focusing on these steps, organizations can better protect their AI systems and data when using AI tools, ensuring a secure and compliant work environment that leverages AI technologies effectively and responsibly.<\/p>\n

                          Ethical Considerations in AI Adoption<\/h2>\n

                          Ethical considerations play a vital role in AI adoption, as organizations must ensure AI technologies do not harm users or stakeholders or perpetuate harmful biases. There is an important distinction between the ethical concerns with using AI versus the ethical considerations for creating an AI model.<\/p>\n

                          This blog is limited to ethical concerns with using AI. Some key ethical considerations to address include:<\/strong><\/p>\n