by Charlie
A recurring trend with most technologies is that they are often widely used before the relevant laws are fully established. Governance of technologies – especially those that are widely used – is essential to protect people, companies and their data from misuse.
Here are a few basic points to consider when thinking about your AI governance model:
consider the strategy for using AI
What is your plan? What are your objectives? Ask yourself if the company really has a business case for AI, i.e., will AI embedded in your product or service have a meaningful impact on your customers? If the answer is no, then it’s probably not worth the effort and cost to develop it.
Develop an AI usage monitoring policy
If the answer is yes, then a second consideration should be the development of a policy or statement that defines how AI will be used within the company and by whom. This foundational document can take the form of a formal policy that clearly states why AI is being used, by whom, and for what purpose. Policies tend to be more prescriptive and specific, setting out how the technology must – not should – be used. Your policy can also refer to industry standards to serve as a benchmark.
Consider developing guidelines for AI use
Alternatively, you can develop a guide, which traditionally lists recommended usage and best practices. There are advantages and disadvantages to both approaches. Depending on your industry, the level of regulation you are subject to, and the type of data your company uses (e.g., B2C or B2B), you may choose to use guidelines so as not to unduly restrict innovation or experimentation.
Create a portfolio of AI documents
Whatever you choose, the goal is to create a series of documents that provide as much guidance as possible to employees on how to use the new technology, which will help them to create feature-rich products and services in an ethical and responsible way when using data.
Create a legal compliance framework
Next, make sure that the legal basis for your data processing is solid. If you are processing the data of EU citizens, in particular, find the most appropriate legal basis for your situation in accordance with Article 6 of the GDPR.
Identify AI decision makers
Another important task is to create an AI approval process, including the designation of decision makers.
The ideal AI governance framework should be positioned between the conceptualization and operationalization phases, which will ensure that any teams, committees, or forums set up to evaluate ideas and use cases are able to adopt a holistic and cross-functional perspective. With this approach, they can comprehensively assess the unique risks that AI poses to your business model and determine which initiatives should move forward to production.
