As artificial intelligence (AI) continues to shape our world, building a responsible AI team, including technical and non-technical team members, is crucial. This team of experts collaborates to develop, deploy and manage AI systems ethically. Let's explore the essential steps for creating such a team:

1. Define your AI strategy

Before assembling your team, start with clarity. Define a well-structured AI strategy that outlines project goals, scope, ethical considerations, and success measurements. Ensure alignment with your organization's overall business strategy and values.

2. Identify key roles and skill sets

Your team should include diverse experts:

  • Data scientists: Proficient in machine learning, data analysis, and statistical modeling.
  • AI engineers: Skilled in implementing AI algorithms, model deployment, and infrastructure.
  • Domain experts: Individuals with industry-specific knowledge. For example, physicians when developing AI for healthcare.
  • Security experts: Responsible for threat mitigation, vulnerability assessment, and secure development.
  • Privacy specialist: Individual with expertise in privacy policies and compliance with regulations. Skilled in data protection and safeguarding personal data, including ethical data handling.
  • Ethics and compliance specialists: Responsible for ensuring ethical AI practices.
  • Project managers: Facilitate coordination and communication with an agile focus.

3. Recruit top talent

Look for team members with:

  • Diverse skill sets: A mix of technical expertise, domain knowledge, and ethical awareness.
  • Inclusion: Prioritize diversity to bring varied perspectives. Inclusion goes beyond ethnicity and gender; inclusion also means those with various experience levels.
  • Passion for responsible AI: Seek those who value ethical considerations and societal impact.

4. Provide ongoing training and development

AI evolves rapidly, so invest in continuous learning. Additionally, team members should understand responsible AI principles, including ethical and bias considerations.

5. Foster collaboration and communication

Encourage cross-functional collaboration between data scientists, engineers, and domain experts. Regular meetings allow for sharing insights, addressing challenges, and aligning goals.

6. Provide access to resources and tools

Equip your team with the necessary hardware, software and/or cloud resources. Utilize the WWT AI Proving Ground to determine which hardware and software best fit your AI project. Consider the mid-term and long-term cost of utilizing on-premise hardware and software vs. public cloud providers. 

Always leverage ethical AI frameworks and guidelines for responsible development. Remember, a responsible AI team combines technical expertise with ethical awareness. By fostering collaboration and staying informed, you'll build a team that drives innovation while ensuring a positive societal impact.

WWT has been helping customers with AI for over ten years.

Feel free to share this guide with your colleagues and peers as you embark on your responsible AI journey!