124 - The PiCAA Framework: My Method to Generate ML/AI Use Cases from a UX Perspective
Aug 22, 2023
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In this podcast, the speaker introduces the PiCAA Framework for generating ML/AI use cases from a UX perspective. They emphasize the importance of brainstorming ideas, considering human factors, and involving cross-functional teams. The Pico and PiCAA frameworks are discussed, along with examples of AI use cases. The risks of automation and the importance of a human-centered approach are also highlighted.
The Pika framework helps generate AI use cases by combining verbs with 'how might we' to spark ideas, emphasizing the importance of understanding business objectives and involving cross-functional teams in ideation workshops.
Before implementing the Pika framework, it is crucial to consider the human perspective, including users' pain points and biases, focusing on generating a high volume of ideas without judgment, and prioritizing small AI wins and human decision-making.
Deep dives
The Pika framework: A creative exercise for AI use cases
In this podcast episode, the host introduces the Pika framework, which is a creative exercise for imagining AI use cases within a business or product. The framework consists of a collection of verbs combined with the sentence 'how might we' to generate potential ideas. The framework includes verbs such as predict, classify, automate, and augment. The host emphasizes the importance of understanding the business objectives and involving cross-functional teams in ideation workshops or design jams. The goal of the workshop is to generate a large volume of ideas, not necessarily focusing on feasibility or implementation at this stage. Additionally, the framework highlights the value of considering human factors and the potential impact of AI solutions.
Considerations for AI solution ideation
Before implementing the Pika framework, the host recommends understanding the customer's business objectives and considering the human perspective. This involves being familiar with users' pain points and biases, and intentionally biasing solutions towards solving their problems. In the discussion, the host also emphasizes the importance of generating a high volume of ideas without judgment, as it can lead to more concrete and realistic solutions. Furthermore, the host explains the need to focus on small AI wins, rather than aiming for large-scale automation. Finally, human decision-making and repetitive digital tasks are identified as areas where machine learning and AI can be particularly beneficial.
The significance of human impact and cautionary steps
The podcast episode concludes by highlighting the importance of considering the potential negative impacts and risks associated with AI solutions. The host suggests conducting black mirror testing, abuseability testing, and engaging red teams to assess potential issues. While emphasizing the focus on generating value with AI, the host warns against putting the cart before the horse and advocates for problem-centered thinking over a solution-first approach. Considering both economic value and the well-being of the humans in the loop, the host emphasizes the need for a human-centered approach to AI development and implementation.
In this episode, I give an overview of my PiCAA Framework, which is a framework I shared at my keynote talk for Netguru’s annual conference, Burning Minds. This framework helps with brainstorming machine learning use cases or reverse engineering them, starting with the tactic. Throughout the episode, I give context to the preliminary types of work and preparation you and your team would want to do before implementing PiCAA, as well as the process and potential pitfalls you may run into, and the end results that make it a beneficial tool to experiment with.
Highlights/ Skip to:
Where/ how you might implement the PiCAA Framework (1:22)
Focusing on the human part of your ideas (5:04)
Keynote excerpt outlining the PiCAA Framework (7:28)
Closing a PiCAA workshop by exploring what could go wrong (18:03)