In an era of Artificial Intelligence (AI), the importance of AI governance cannot be overstated. As organizations increasingly rely on AI, the need for a comprehensive governance framework to ensure ethical, transparent, and effective AI utilization becomes paramount. This blog delves into the essence of AI governance and the intricacies of content governance in the AI era, offering insights and strategies for navigating this complex landscape.
With so much information available about Governance when it comes to Artificial Intelligence (AI), people have been turning to AI to help them collate and provide a suitable response. And why not, this is one of the benefits we’ve been promised, AI that will help us to be more efficient and productive. Enabling us to focus on the higher value tasks. So, what’s the problem, we’re just doing what we’ve been told to do, do more with less.
Well, in principle there isn’t a problem, for knowledge workers this is an evolution of search and how we access large volumes of useful (and some not so useful) information. We can apply our own knowledge, combine, and refine, reword, and tailor the returned information into something that is relevant and applicable for our purposes. This is often done with our tacit understanding of the purpose at the forefront of the process.
For example, to write this article an initial decision needed to be made, who is the target audience for it? AI Governance can be about the management and auditing of AI data and the models applied. That is relevant to any organization developing AI solutions. We could talk about the importance of including the techniques used to train the models (e.g., human-assisted), parameters applied and the testing metrics. Setting the context that this article was to be about the governance of the outcomes when it comes to using AI generated content.
Understanding AI governance
AI governance is the holistic approach to managing and regulating AI systems within an organization. It encompasses policies, procedures, and practices that ensure AI is used responsibly, ethically, and effectively. The goal is to create a balanced ecosystem where AI's benefits are harnessed while minimizing its risks and ethical implications.
Why AI governance matters
- With AI's ability to influence decisions, ethical concerns such as bias, discrimination, and privacy violations become critical. Governance ensures these issues are addressed proactively.
- AI governance aligns AI initiatives with existing legal frameworks and data protection regulations, mitigating legal risks and potential fines.
- By setting clear guidelines for AI deployment, governance frameworks ensure AI systems operate within intended parameters, maintaining operational integrity and trust.
- Ethical and transparent AI practices foster public trust, crucial for maintaining and enhancing an organization's reputation.
Key components of effective AI governance
The below summary provides an outline of best practice
- Ethical AI principles: Develop a set of core ethical guidelines that AI initiatives must adhere to, ensuring fairness, accountability, and transparency.
- Cross-functional governance structures: Establish a governance committee comprising diverse stakeholders, including legal, ethical, technical, and business representatives, to oversee AI deployments.
- Comprehensive policy framework: Implement policies covering AI development and deployment stages, focusing on data quality, privacy, security, and ethical use.
- Transparent decision-making: Ensure AI systems' decisions are explainable and transparent, facilitating auditability and accountability.
- Continuous monitoring: Regularly assess AI systems against performance metrics and ethical standards, adjusting governance policies as AI technologies and societal norms evolve.
- Stakeholder engagement: Engage with employees, customers, regulators, and other stakeholders to gather insights and address concerns related to AI use.
- Employee awareness: Educate employees about AI governance policies, ethical considerations, and their role in upholding governance standards.
The importance of content governance for AI
Content governance encompasses the policies, processes, and standards that guide the creation, management, and dissemination of digital content. In the context of AI, it extends to overseeing how AI technologies are applied in content-related activities, ensuring they align with organizational objectives, ethical standards, and regulatory requirements. Effective content governance for AI is crucial for several reasons:
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Ensuring quality and accuracy: AI-generated content must meet the same standards of quality and accuracy as human-created content, necessitating strict governance frameworks.
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Ethical considerations: From combating AI-generated misinformation to addressing biases in content recommendations, ethical considerations are at the heart of content governance.
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Compliance and legal risks: As content laws evolve, organizations must navigate copyright issues, data protection regulations, and other legal complexities associated with AI-driven content.
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Brand integrity and trust: Maintaining a consistent brand voice and ensuring trustworthy content are vital for preserving brand integrity in the digital age.
Governance in relation to the use of AI content in your organization
Not only is the topic important, but the context. Without context, this article could have been about people building AI solutions, those looking at the regulation for AI and/or people who want to use it to help them be productive. By the way, you are in the right place if you are interested in governance in relation to the use of AI content in your organization.
Governance regarding AI generated content provides us with a framework in which to work safely. It ensures that knowledge workers can safely find, discover, and use content with tools they have available. Governance provides us with the confidence that the information we are using is appropriate.
Information governance should be something you are already doing, and it now needs to be extended to how you manage AI generated content. If you don’t have information governance policy, processes and procedures in place, best start now!
If you read the AI news grabbing headlines, the recommendations are simple:
- Know your sources. Where has the information come from, is it a ‘trusted’ source, how has the AI model been developed/trained?
- Understand what you asked for. What context did you provide, is the available content reflective of the topic, is the topic unusual, are there proven citations from the sources?
- Validate the facts and appropriateness with others. Is it factually correct, evidence of accuracy, is it free from bias, is it ethical, does it align with our company culture?
- Review and refine before publishing. Is it engaging, does it read well, does it align with your company language?
- Regulate and set standards. Does it comply with any privacy obligations, is it being used appropriately (who ‘owns’ it, copyright, open-source agreements, personal data protection, is AI recognized as a contributor), is it still valid to use/keep?
- Understand what it costs. Processing Large Language Models (LLM) isn't cheap. There is a considerable amount of compute power being consumed to produce the output. Do you know how this cost is being equated, are you getting good value from what people are asking and the outcomes they achieve, and how are you balancing this against your organizations net zero strategy?
There are limitations to how much you can achieve of the above with AI. There are certain external risks that we will have limited control over such as knowing the sources and the algorithm that makes the decision on what to present. Though we can reduce and manage the risk by putting in controls such as getting better with our prompts to mitigate using the wrong information. Already looking for a Prompt Engineer/Writer to get the best out of AI? We’ve all got better using search (and how search got better understanding us) and we will need to upskill with AI sourced and generated content.
Extending your information governance framework to include AI is essential. Acknowledging and treating with a risk-based approach may be one way of tackling the problem. Putting in place controls to minimize the likelihood and consequence of each risk.
AI scenarios to strengthen governance practices
When it comes to extending and strengthening your governance practices, it is worth considering the different scenarios of where AI may be applied. Here are some examples:
- Give me more think time. Make meetings more effective, organize, summarize, track actions, targeted output, notify me of anything I need to follow-up.
- Help me get the right answer. Refine and reduce the information I need to read to provide me with the best possible answers.
- Get me started. Provide an initial draft that I can enhance and produce quality content efficiently.
- Do mundane tasks for me. Automate the transfer of unstructured data into meaningful structured reporting data.
- Analyze and find patterns/trends for me. Look at large data samples for patterns and predict potential outcomes or interesting correlations.
Hence the governance framework required will need to adapt and evolve to manage different working scenarios, depending on where and how you apply AI.
Leveraging Atlas for content governance in the AI era
Atlas offers a powerful platform to tackle the challenges of AI-driven content governance head-on. With its integrated governance tools, Atlas helps organizations:
- Centralize content management: Atlas provides a unified repository for all content, simplifying governance and ensuring consistency across AI-generated and human-created content.
- Governance by design. Atlas is For example, to reduce the burden of compliance any content added to Atlas is categorized based on where it is saved. This also improves its findability as well as ensuring appropriate use and retention. Thus, people are confident in the use of the content and ensures that they have the right information and can use it appropriately. Content that is being generated using AI needs to follow the same rules and the people creating content using AI need to be clear on their role and responsibilities in this process.
- Enhance data security and compliance: The platform protects sensitive data being used by AI.
AI related articles
There are plenty of excellent articles available on the subject and some ‘words of warning’ as well. Here is a selection worth a read:
AI overview
What can AI help with?
What can go wrong and how do we regulate AI?
View all articles by this author
