W5: Eapen et al. (2023) Flashcards
(15 cards)
Innovation
Has become the cornerstone of competitive advantage. Thus, the traditional model of corporate-led product and service development is being re-evaluated
Democratisation of innovation
A concept that represents a paradigm shift towards harnessing the collective creativity and insights of users. This approach, facilitated by digital platforms, invites individuals from across the world to contribute to the innovation process, challenging the notion that breakthrough ideas can only emerge from within the confines of corporate R&D departments. However, as organisations open their doors to a wider pool of contributors through crowdsourcing and innovation contests, they encounter a set of unique challenges; overwhelming influx of ideas, biases of domain expertise, and difficulties of integrating disparate customer inputs into a unified solution
Paper’s purpose
Explores the potential of involving users in the innovation process, the hurdles that organisations face in doing so, and the strategies that can be employed to overcome these challenges. It aims to shed light on how democratisation of innovation can lead to more inclusive, user-centred products and services in today’s dynamic market landscape
Evaluation overload
A primary concern, where the influx of ideas from these open calls exceeds and organisation’s capacity to effectively assess and prioritise them, leading to potentially valuable contributions being overlooked
The curse of expertise
Presents a paradox where domain experts, while adept at identifying feasible ideas, may exhibit resistance to truly novel concepts due to their entrenched knowledge and expectations, limiting the scope of innovation. This expertise bias can be overcome through generative AI by generating atypical designs, allowing designers to transcend conventional thinking
Generative AI tools
Address challenges by combining or merging numerous ideas to produce stronger ones, aiding in the genration and refinement of innovative concepts. The article outlines 5 key ways generative AI can enhance the innovation process
Trisociation
Combining distinct entities to form new business concepts, thereby enabling rapid exploration of diverse designs. Such techniques are used to facilitate idea generation in large language models such as ChatGPT
Divergent thinking
Fostered by generative AI by creating associations between disparate concepts to generate novel outputs
Design fixation
Overreliance on standard forms
Functional fixedness
Inability to see beyond traditional uses
Einstellung effect
Where previous experiences hinder new problem-solving approaches
Generative AI
Can significantly aid in the front end of innovation by improving idea specificity and assisting in their evaluation. Large language models can offer balanced assessments of different concepts, analysing pros and cons. They can also evaluate ideas against multiple dimensions of creativity, incl. novelty, feasibility, specificity, impact, and workability
Idea refinement
The effective combination of numerous individual ideas into more robust and comprehensive solutions. A task where generative AI can provide substantial support. AI tools can first elaborate on individual concepts and then merge these into a single, coherent program or proposal, thereby creating a stronger overall concept
Co-creation
Enhanced by generative AI by enabling easier and less expensive collaboration between a company’s designers and its users, as well as among users themselves. Businesses can e.g. provide users with AI tools to generate their own designs
Stable Diffusion
AI tool that can be used for iterative concept development, such as generating initial product designs and then asking the AI to reimagine them with specific thematic variations. This can also involve AI generating visuals from textual descriptions of product details, fostering a dynamic and collaborative design process
