Examining the skillset of AI designers
Executive design recruiter Adam Perlis shares insights about the skills and experiences companies are screening for as they build their AI design teams
Note from Emily: Recently any conversation I have with other design leaders eventually comes around to the question: how do our roles and our teams need to shift in a GenAI world?
To answer this question, I reached out to Adam Perlis, a seasoned design leader in his own right and the CEO of Academy. In addition to providing design staffing and recruiting, Adam has worked with top design leaders and their teams to identify designers in AI who can make an impact. He shares his thoughts below on the evolving AI UX skillset, and describes what it looks like to interview as or recruit an AI designer.
As AI technologies continue to advance, the demand for skilled designers who can navigate the complexities of AI-driven design is on the rise. However, the defined role of “AI designer” is nebulous.
There is not just one type of AI designer. AI has different facets. Just as we differentiate between the skills and experiences needed to thrive as a designer in SaaS vs. E-Commerce, different aspects of AI design will require a different set of skills and expertise.
Three types of AI Designers
1️⃣ Designers incorporating AI
As AI tools become more commonplace in our processes this may eventually be simply titled “designers.” Today, hiring a designer with experience working with AI tools can help upskill your entire team and establish them as a future-oriented practices lead.
These designers incorporate AI-powered tools into their workflow to enhance creativity, efficiency, and problem-solving capabilities. They use AI for tasks such as generating design options, automating repetitive tasks, and analyzing user data to inform design decisions.
Example tools: ChatGPT, Adobe Photoshop's AI features, Canva's Magic Write, Framer AI Designer, and image generators like Midjourney or DALL-E.
Emerging skills: Traditional design skills, proficiency in design software with AI features, understanding of how to integrate AI into the design process, and the ability to interpret and apply AI-generated insights.
2️⃣ Designers building AI tools
These designers focus on creating tools and applications that leverage foundational AI technologies like natural language processing (LLMs), computer vision, or generative adversarial networks (GANs) for image generation. They design user interfaces, interactions, and experiences for AI-driven products, ensuring that the AI's capabilities are accessible and user-friendly.
Example tools: Chatbot design platforms, AI-powered image editing software, AI-driven analytics tools, and custom image generators.
Emerging skills: Strong understanding of AI capabilities and limitations, user experience design, interface design, prototyping, and collaboration with AI researchers and engineers.
3️⃣ Designers of foundational AI interfaces
These designers specialize in creating the interfaces and interaction paradigms that enable humans to effectively interact with AI technologies. They focus on designing the user experiences for platforms that utilize AI, such as chat interfaces for LLMs, control panels for image generators, voice interfaces for voice-activated AI, or spatial interfaces for immersive AI experiences.
Example tools: These designers will work closely with engineers, or may be design engineers themselves, because the prototyping tools to unblock their work often don’t exist yet. Existing tools include Voiceflow and other platforms for conversational design, developing voice command systems for AI assistants, and crafting spatial interactions for AI in virtual or augmented reality.
Emerging tools: Deep understanding of human-computer interaction, user experience design, familiarity with AI technologies, and the ability to create interfaces that make complex AI functionalities accessible and intuitive to users.
“Designers need strong interaction and microinteraction chops to figure out how to squeeze AI work into an existing canvas, unlike foundational models that have an unlimited canvas to flex AI.”
— Joel Lewenstein, Head of Product Design @ Anthropic.
Evaluation Criteria
Hiring the right AI designer requires a comprehensive evaluation of their skills and abilities. These criteria ensure that the designer not only possesses the necessary technical skills but also demonstrates critical thinking, adaptability, and ethical considerations in their approach to AI design. All types of AI designers will require these skills to navigate the ambiguity of this shifting domain.
Critical Thinking:
Demonstrated ability to critically evaluate design issues, particularly in AI-driven and dynamic environments where outcomes are unpredictable.
Proficiency in navigating ambiguity and making informed decisions.
Ability to anticipate and address failure states in non-deterministic models.
Adaptability:
Strong adaptability in handling various design scenarios.
Can design effectively in real-time environments and manage the evolving nature of AI-generated content.
Ethical Consideration:
Deep understanding of the ethical considerations in AI tool design.
Track record of integrating ethical principles into the design process to ensure responsible and inclusive outcomes.
Technical Proficiency:
Advanced knowledge of AI technologies, including LLMs, generative AI, and other relevant tools.
Proficiency in interaction design and micro-interactions is desirable.
Demonstrated expertise in using design software such as Figma and Framer for product design.
Problem-Solving:
Proven ability to tackle complex design challenges, as evidenced by a portfolio, design exercises, or case study presentations.
Displays a methodical approach to problem-solving and an ability to deliver innovative solutions.
Communication Skills:
Exceptional communication skills, particularly in articulating design decisions and rationale.
Can clearly explain their approach to navigating ambiguous design challenges and justify their design choices.
"It's important to hire designers who can think through failure states and design for non-deterministic AI systems."
— Abhinav Sharma, Director of Product Design @ Scale AI
Interview Process
Interviewing for an AI designer role will be familiar in some ways and quite different in others. Companies will want to assess your hard skills, but also understand how you adapt to a shifting landscape and navigate through uncertainty. The interview process will vary from company-to-company, but generally you can expect something that looks like this.
Hiring Manager Phone Screen
A review of the candidate's portfolio to assess their experience and design skills, particularly in projects related to AI or complex systems. Samples questions may include:
How have you started to incorporate AI into your workflow or day-to-day life?
This question helps an interviewer evaluate how much exposure a designer has to AI and how familiar they are with AI products and design.Can you describe a project where you had to design a feature or product in a space that was new to you? How did you approach understanding and solving the problem?
Designing with or for AI requires designers to operate in a space that is unfamiliar and regularly changing. This question allows interviewers to understand how the designer approaches ambiguous projects and how likely they are to thrive in this environment.Can you describe a product or company that has faced an ethical dilemma using AI? What did they do? How would you assess their approach?
Interviewers may want to understand how people identify ethical dilemmas, and their knowledge of how to solve for them. Even if you haven’t experienced an ethical dilemma yourself, it’s helpful to be prepared to represent how you would approach a similar situation.
Hiring Manager Interview
A one-on-one interview focusing on the candidate's experience, approach to design, and understanding of AI in the design context. This can include questions about how they've dealt with ambiguity or working through failure states in non-deterministic design projects and their approach to ethical considerations in AI design.
Panel Interview / Case Study Presentation
The candidate presents a case study from their portfolio, emphasizing how they navigated through a fuzzy design problem. The interviewers can ask probing questions to understand the candidate's thought process and decision-making.
1:1 Team Member Interviews
Team Fit Interview: A discussion with potential team members to assess cultural fit and the candidate's ability to collaborate effectively in a team environment. Be prepared to meet with engineers and data scientists, who will be likely collaborators.
Collaborative Design Exercise: A live design exercise where the candidate is presented with a hypothetical, AI-related design problem. You may be asked to think aloud as they work through the problem, showcasing their critical thinking and problem-solving skills.
Collaborative Design Exercises
Practical exercises play a vital role in the interview process for AI designers. Use these sample collaborative design exercises to understand how you might frame your experience through the lens of AI design problems. These exercises offer insights into the candidates' creativity, ability to tackle complex challenges, and their proficiency in designing user-centric AI solutions.
Sample framing:
As part of the interview process, you will be paired with one of our product designers or product managers to work on a collaborative design challenge. You will be presented with several briefs to choose from, and you will have one hour to work on the challenge.
Please note that this challenge is not intended for you to complete the task fully. Instead, we want to see how you approach problem-solving and how you work collaboratively with a team member. You are free to utilize any collaboration tool of your choice, such as Figma, Miro, or Mural, or any other tool you find useful.
Please choose from one of the challenges below:
AI-Powered Personal Stylist
Scenario: You're designing an AI-powered personal stylist app that suggests outfits based on the user's wardrobe and preferences. However, the app sometimes suggests combinations that don't match the user's style or the occasion.
Question: How would you design the AI's logic to better understand the user's style and the context of the occasion? What mechanisms would you implement for users to refine the AI's suggestions?
Smart Grocery List Assistant
Scenario: You're developing a smart grocery list assistant that uses AI to suggest items based on the user's purchase history and dietary preferences. However, it occasionally recommends items that the user dislikes or is allergic to.
Question: How would you design the AI to accurately capture and prioritize the user's dietary restrictions and preferences? How would you enable users to provide feedback on the suggestions and correct inaccuracies?
AI-Driven Fitness Coach
Scenario: You're working on an AI-driven fitness coach app that creates personalized workout plans. However, the app sometimes suggests exercises that are too difficult or not suitable for the user's fitness level.
Question: How would you design the AI to better assess the user's fitness level and adjust the workout plans accordingly? What options would you provide for users to modify the suggested workouts?
Automated Travel Itinerary Planner
Scenario: You're creating an automated travel itinerary planner that uses AI to suggest travel itineraries based on the user's interests and budget. However, the planner occasionally proposes impractical itineraries with unrealistic travel times or incompatible activities.
Question: How would you design the AI to ensure the practicality and feasibility of the suggested itineraries? How would you allow users to customize the itinerary and make adjustments based on their preferences and constraints?
Final thoughts
Hiring the right AI designer is a critical process that requires careful consideration of various factors–many of which will vary depending on how AI relates to the role.
By understanding the different types of AI designers, evaluating candidates based on key criteria, and implementing a structured interview process with collaborative design exercises, organizations can ensure they select individuals who are not only technically proficient but also capable of navigating the complexities of AI-driven design.
Ultimately, the success of AI projects hinges on the creativity, adaptability, and ethical approach of the designers involved, making the hiring process a pivotal step in shaping the future of AI innovation.
PARTICIPATE IN THE DISCUSSION: Share your thoughts and observations on LinkedIn in the conversation here.