Maneesh Juneja is a Planetary Health Futurist who explores the convergence of emerging technologies to see how they can make the world a healthier and happier place, both for humans and for the natural systems that support humanity’s existence. He looks at these technologies in the context of socio-cultural, political and economic trends, helping organisations around the world to think differently about the future.
He is passionate about ensuring that the choices we make in society today result in a better future, not just for the privileged few, but for everyone. In the quest for Net Zero, how we can restructure the way we live, work and play so that we have the best possible chance of a “just transition” to a green economy?
Building upon over a decade of working in digital health, one of his core areas of research is looking at how the entire healthcare industry can become sustainable, from an environmental perspective.
How can we continue to innovate, in a way that will leave the planet in a better state for future generations? Who will drive innovation in the 21st century, humans or autonomous agents powered by AI, or a combination of both? What skills do workers need to stay relevant in the future, whether it’s helping to combat climate change, or adapting to the continued automation of highly skilled work by algorithms?
In 2022, his views on the future of 3D printing of human organs have been featured as part of the Netflix docuseries, The Future Of.
In a career spanning nearly three decades, Maneesh has worked with data to improve decision-making across a number of industries. From supporting the Whitehall study at University College London, managing the Tesco database at DunnHumby, working with the world’s largest U.S. health insurance claims & European EHR databases at GSK R&D, and most recently, working as a Digital Health Futurist.
Health is what happens to us in between visits to the doctor. We can’t just keep building more hospitals and hiring more doctors and expecting everyone to be healthier. That’s not a sustainable model. The pandemic has made human health an even bigger priority. There are so many new business opportunities for organisations outside of healthcare, to make an impact on our health, enabled by technology and data. How can you look beyond traditional boundaries to develop new products and services that can impact our health whilst helping your organisation to stay relevant during an era of massive change and disruption?
We talk about Artificial Intelligence (AI) at two ends of a spectrum, either utopian or dystopian future scenarios. Either all of humanity’s problems will be solved or we will all be enslaved by tyrannical algorithms. Neither scenario is realistic. So, how do we find a middle path that is agile enough to adapt to emerging technology but can also integrate with our policies, processes and people? Many are rushing to invest huge amounts in collecting more data and building new types of AI, but are they missing critical steps in this race to be first to market? What do organisations need to be doing to ensure their desire to innovate with AI doesn’t cause harm and doesn’t lead to losing the trust of their customers?
Anyone working in healthcare knows the difficulties of innovating within a risk averse, complex and highly regulated sector. However, emerging technologies, economic/social trends and a desire from patients to have more access, agency and autonomy are challenging the status quo in the healthcare sector. Does all of this mean that we will need fewer doctors and smaller hospitals in the future? Will some patients prefer to interact with a machine for healthcare needs rather than a human being? Are we heading for a world where AI monitors us 24 hours a day constantly checking for signs of disease? Where will the innovation in healthcare come from? From the sector, from startups or perhaps from patients themselves?
Data driven decisions are increasingly the norm across all layers of society, whether we apply for a bank loan, use a health app to check our symptoms, or have our faces scanned by facial recognition algorithms. Who should be making these decisions based upon data? Humans, or algorithms, or both? Is it really possible to build algorithms that are neutral and unbiased? How should your organisation approach data driven decision making from an ethical perspective? Does the use of data mean that privacy has to be infringed or are there new ways of doing analytics that also preserve personal privacy? Ultimately, how can we work together to build a data driven future that we can trust.
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