Transformative technologies are contributing solutions to major human and environmental challenges, and are expected to play a greater role as disruptions associated with global population and climate change increase. At the same time, these technologies also face challenges themselves in terms of the design and uptake of responsible and equitable solutions. Discussions between experts across technologies and sectors to exchange ideas and lessons learned will multiply their positive effect.

Perhaps a surprising pair to some, there are interesting parallels between technologies and tools in the fields of genomics and smart cities. Genomics is the science that aims to decipher and understand the entire genetic information of an organism (plants, animals, humans, viruses and micro-organisms included) encoded in DNA and corresponding complements such as RNA, proteins and metabolites. Smart cities is an umbrella term that captures digital technologies being used to improve the efficiency of city services and enhance the quality of life and prosperity of citizens and businesses.

In the development and adoption of genomics, there are certainly challenges, such as sharing genomic data between institutions. But there are experiences and lessons learned that can assist in and inform the responsible uptake of other transformative technologies in the 21^st century. What insights can be derived from the field of genomics that can be used in other transformative technologies such as in smart cities? Two of the key issues facing future smart cities are collaboration between stakeholders and the application of data.

Collaboration is key

First, competing multi-stakeholder perspectives around the development and adoption of any technology is a common challenge. The development of transformative technologies often creates tensions among stakeholders as researchers, industry and the public may have different perspectives and priorities. The Sidewalk Labs project in Toronto is a vivid example of how the public’s skepticism around the use of data helped to scuttle plans for the futuristic smart city on Toronto’s eastern waterfront. The Alphabet-backed project clearly demonstrated the need to bridge competing views. Building strong and clear collaborations across the pipeline – from development to adoption of a technology – are crucial so stakeholders can co-create what they envision as the best solution.

An important milestone in the evolution of genomics is the Human Genome Project (HGP), a large international collaboration to sequence the human genome. Launched in 1990 and completed two years ahead of schedule in 2003, the HGP is still the largest collaborative biological project and resulted in the first complete human genome sequence. During the project, teams from the six participating countries were sharing data with the rest of the international researchers on a daily basis, an unheard-of level of collaboration in other fields. The demonstration of such a highly collaborative and open culture continues to benefit the global community today. It’s evident with the COVID-19 pandemic, as scientists and experts across the globe collaborate in trying to understand and map the virus and its variants.

The full potential of genomics is, however, limited by the competing aspects of commercializing technologies, and the existence of regulatory and other obstacles, which prevent a broader sharing of genomic data (even within Canada). But the field at large remains collaborative and focused on its premise to help humanity.

Genomics and smart cities face similar opportunities and challenges as they try to innovate. There are several examples of success across sectors in both fields. Human health and environment are two areas where both genomics and smart city technologies have offered tools that have improved our lives. For example, genomics is the field behind COVID-19 tests and vaccines, and many groundbreaking discoveries around animal and human diseases such as cancer. Smart city technologies have improved services such as public transport and environmental monitoring. As the public becomes more aware of and involved in the use of these technologies, questions around open/private data, intellectual property, governance, and regulation are some of the main common challenges.

Equitable data

Another important aspect of the parallel trajectories of these two fields is in relation to the use of data. There are important lessons learned in both genomics and smart cities for the collection, curation and ownership of data assets.

The application of data assets and tools raises important questions in any technology. At a fundamental level, who benefits and who gets left out? In the case of genomics, important debates around the under-representation of certain groups in research have led to projects that focus on generating and using data of otherwise excluded populations. Silent Genomes, for example, specifically reduces health-care disparities and improves diagnostic success for children with genetic diseases from Indigenous populations.

For smart cities, there is an opportunity to use open data to inform urban planning, for example, improving mobility services for vulnerable populations. Specifically, data can shed light on the many ways people and goods get around and help public transit to increase the frequency, quality, and overall mobility for low- and medium-income households and improve access to essential amenities for citizens who need them the most. This is a very important aspect for the successful and responsible adoption of solutions, and other transformative technologies should move toward the collection and use of more diverse data to ensure that solutions produced are more equitable and benefit the whole of society.

There is also a very active discussion around bias in data, algorithms, and the selection of data samples in studies. All these aspects influence how each technology is used, what kind of solutions are offered and to whom, and ultimately who benefits from them. In the field of genomics there are important lessons learned for addressing the diversity of needs at the individual and community level, such as with Indigenous and other marginalized populations. There is an opportunity for these lessons to be transferred to challenges that smart cities face in terms of data security and privacy for citizens, as was evident in the case of Sidewalk Labs in Toronto.

Conclusion

The broader theme of responsible innovation incorporates all aforementioned aspects in the roadmap to a successful and equitable adoption and use of transformative technologies. Citizens, industry, researchers, and governments should all work together in co-designing solutions with social and economic sustainability in mind. Responsible innovation departs from conventional innovation by including all stakeholders – especially those who are otherwise marginalized – in the whole pipeline of innovation, from inception to reaping the benefits of uptake and commercialization of a new tool.

As we move further into the 21^st century, the experiences in every technology should inform the practices of others. Open interdisciplinary dialogues are important in sharing lessons and solving common challenges. These discussions are not new to the fields of genomics and smart cities, but many emerging technologies, such as artificial intelligence and robotics, face these challenges. Discussions across technologies and sectors are more important now than ever.