We’re thrilled to open a call for creative briefs! The Creativity for Scientific Change (CSC) project is commissioning a creative visual communication project to explore and interpret the socio-ethical considerations surrounding the development and use of synthetic data in machine learning (ML) research for medicine.
We are looking for proposals from designers, art directors, artists, and illustrators at all career stages. If you have an exciting idea to help us create an inspiring strategy that resonates with both ML scientists and the public, we want to hear from you!
The goal is to inspire reflection and motivate people to actively participate in an online forum, sharing thoughts and perspectives on the socio-ethical implications of synthetic medical data.
How to apply:
- Read the full brief below.
- Feel free to reach out with any questions.
- Submit your proposal along with examples of previous work by February 3rd 2025 to Daniela Boraschi at db889@cam.ac.uk.
- Award grant: £10,000
We’re excited to see your creativity and can’t wait to work together to bring this important topic to life!
Framing Ethical Futures
Using Posters to Connect Scientists and the Public on Medical Synthetic Data
“It’s surprising that there’s a significant lack of discussion around synthetic data and the ethical questions it raises. Even within the research community, we are struggling to address these questions, let alone bring them to the public. As a pioneering lab in synthetic data and ethical thinking, it’s crucial for us to put together a framework for addressing these questions within the research community. We can then expand our focus to include the public, which is even more important but also more complex (…) I look forward to collaborating with all of you on this vital work. It is essential that we take action for the benefit of everyone – our research communities and the public. This needs to be done urgently and thoughtfully”.
Machine Learning scientist
About
Many people know about generative artificial intelligence technologies (GenAI) like ChatGPT, but GenAI extends beyond chatbots to include various less familiar yet impactful data generation methods. ML scientists can now develop algorithms to identify patterns in medical datasets, creating ‘synthetic’ data without collecting new information. For example, by using digital health records of existing patients, ML scientists can create synthetic datasets that mimic specific health conditions and the characteristics of various patient groups or individuals rather than needing to recruit participants for clinical studies.
The aim of the creative visual communication project is to encourage collective reflection on some of the ethical considerations that ML scientists encounter daily during their research on synthetic medical data such as:
- Privacy: the delicate balance of maintaining dataset quality, protecting individual anonymity, and minimising the potential security risks of using and sharing medical data for synthesis.
- Representation: the possibility of introducing errors and assumptions about diverse populations during the synthetic data generation process.
- Accountability: the need to establish regulatory oversight to ensure the quality and safety of synthetic data.
- Trust: the confidence (or lack of it) in the synthetic data itself and the outcomes derived from its use in ML medical research and application.
(We have included in this brief a series of links to academic articles and blog posts written by ML scientists where they offer their perspectives on these considerations).
Additionally, the creative visual communication project will seek to inspire active and diverse participation in discussions around these urgent considerations, emphasising the importance of integrating multiple perspectives in ML research to address these challenges.
The project will be supported by a multidisciplinary team, including the CSC project team and ML scientists, who will contribute their expertise and resources to enhance the creative process.
Goals
The goal of the visual communication project is to create an inspiring and cohesive communication strategy that resonates with ML scientists as well as the public, motivating them to participate actively in an online forum (https://pol.is/home), sharing thoughts and perspectives on socio-ethical considerations around synthetic medical data. Specifically:
- Encourage reflection: the project will seek to foster a shift in the fast-paced ML research by encouraging ML scientists to dedicate some of their time to reflect on the socio-ethical challenges emerging from their work beyond discipline-specific requirements, considering broader societal implications.
- Facilitate active participation and public dialogue: the project will seek to inspire reflection on socio-ethical considerations and meaningful interaction through an online forum not only among ML scientists but also between ML scientists and the public.
- Promote diverse perspectives: the project will seek to encourage ML scientists to consider the importance of integrating diverse socio-ethical perspectives in their research practices on medical synthetic data.
Project deliverables
The creative visual communication project will address these goals through eight key deliverables:
- Concept Development. Craft a communication strategy that resonates with and engages scientists and the public, encouraging meaningful participation in the online forum.
- Design Identity. Establish a cohesive design identity that includes an overall look and feel, typeface, colour palette, and layout to ensure all communication elements are visually unified.
- Memorable Slogan. Develop a concise and impactful slogan or phrase that captures the project’s essence and draws attention.
- Short Video Production. Create a high-quality 2-minute video (motion graphic, slideshow, or animation) that explores and communicates a chosen socio-ethical aspect of synthetic data, making the topic accessible and thought-provoking.
- Large Outdoor Posters. Design three large outdoor posters incorporating a QR code, inviting scientists and the public to join the conversation and contribute to the forum.
- Small Indoor Posters. Create three smaller indoor posters with the same QR code, inviting scientists and the public to join the conversation and contribute to the forum.
- Landing Page Design. Develop a landing page that links to the online forum at https://pol.is/home, serving as a gateway for scientists and public members to engage in online dialogue.
- Co-Design Sessions. Participate in collaborative sessions with scientists at key stages (initial ideas, mid-point feedback, and final decisions) to ensure the project aligns with scientific and public interests.
Project references
Please read about the communication campaign “Dear World, Yours Cambridge.” This campaign was designed by the branding agency Johnson Banks and commissioned by the University of Cambridge. We believe it is a great example of an effective design approach to a brief, featuring the development of various design elements such as posters, a website page, and videos (especially the first video under the Instagram outputs) that are similar elements for this brief. Online at: https://www.johnsonbanks.co.uk/work/dear-world-yours-cambridge.
Please also read this series of texts written by AI scientists on synthetic data.
- Harnessing the power of synthetic data in healthcare: innovation, application, and privacy. (Academic article – open access) https://doi.org/10.1038/s41746-023-00927-3
- Synthetic data in machine learning for medicine and healthcare. (Academic article – open access) https://www.nature.com/articles/s41551-021-00751-8
- Ethical considerations on synthetic data in everyday machine learning research for healthcare (part 1&2). (Blog article) https://www.kcesp.ac.uk/ethics-qa-part-1-2-ethical-considerations-on-genai-in-everyday-machine-learning-research-for-healthcare/
- Generating and evaluating synthetic data: a two-sided research agenda. (Blog article) https://www.vanderschaar-lab.com/generating-and-evaluating-synthetic-data-a-two-sided-research-agenda/
- Synthetic data: breaking the data logjam in machine learning for healthcare. (Blog article) https://www.vanderschaar-lab.com/synthetic-data-breaking-the-data-logjam-in-machine-learning-for-healthcare/
How to apply
We inviteproposals from UK-based artists, designers, and creative practitioners at all career stages. To apply, please send your email to Daniela Boraschi at db889@cam.ac.uk and include the following:
- A short outline of your project (max 600 words), which must include how the project and the eight project deliverables will address five key areas of creative development
- Addressing socio-ethical considerations: how will your project creatively explore and interpret emerging ethical considerations on medical synthetic data such as those on privacy, representation, accountability and trust?
- Shaping public understanding: how will the project make them accessible to the general public and the healthcare community and inspire conversations?
- Offering new perspectives: how will the project offer new insights into thinking about the chosen socio-ethical consideration?
- Fostering dialogue and engagement: how will this inspire dialogue between machine learning scientists and members of the public to talk about the socio-ethical considerations?
- Drawing on collaboration: how will you approach co-design collaboration with the machine learning scientists and the CSC project team?
- A project timeline and a proposed budget.
- A portfolio of 3 examples of previous work that demonstrates your ability to engage with complex socio-ethical questions through creative media.
- A link to personal website and social media profiles.
The recipient(s) of the commission must commit to attending meetings and public engagement events related to this commission to introduce their project and reflect on the experience of participating in this project. Detailed information about the timing of the project will be discussed during the interview with selected candidates.