What are the best practices for AI model communication?

1 Define your audience

Before you start communicating your AI model, you need to know who your audience is and what they need to know. Different audiences may have different levels of technical expertise, expectations, and interests in your AI model. For example, a business executive may want to know the business value and impact of your AI model, while a data scientist may want to know the technical details and assumptions of your AI model. Therefore, you should tailor your communication style, content, and format to suit your audience's needs and preferences.

2 Use plain language

One of the biggest challenges of AI model communication is to avoid jargon, acronyms, and complex terms that may confuse or alienate your audience. You should use plain language that is simple, clear, and concise to explain your AI model's concepts, features, and results. You should also define any technical terms or acronyms that you use and provide examples or analogies to illustrate your points. Plain language can help you build trust and rapport with your audience and make your AI model more accessible and understandable.

3 Visualize your data

Another effective way to communicate your AI model is to use visualizations to show your data, insights, and outcomes. Visualizations can help you convey complex or large amounts of information in a more engaging and intuitive way. You can use different types of visualizations, such as charts, graphs, tables, maps, or diagrams, to present your AI model's inputs, outputs, performance, or comparisons. You should choose the appropriate visualization for your data type, purpose, and message and make sure that your visualizations are clear, accurate, and consistent.

5 Highlight your value

To communicate your AI model effectively, you should also highlight its value and impact for your audience. You should explain what problem your AI model solves, what benefits it provides, and what outcomes it achieves. You should also provide evidence and examples to support your claims and show how your AI model compares to other solutions or alternatives. Highlighting your value can help you persuade your audience to adopt or support your AI model and show how your AI model aligns with their goals and interests.

6 Acknowledge your limitations

Finally, you should also acknowledge your AI model's limitations and challenges. You should admit any uncertainties, errors, biases, or risks that may affect your AI model's performance, validity, or ethics. You should also explain how you mitigate or address these limitations and challenges and what future improvements or actions you plan to take. Acknowledging your limitations can help you show your honesty, humility, and responsibility and invite feedback and collaboration from your audience.