Scientists and engineers know that communicating their work in a compelling narrative is crucial to their line of work. It helps people understand and appreciate the complexity of the research and study they have done but the problem is, not many STEM professionals know how to turn their work into a compelling story. What they need to do, according to Dr. Bob Rogers, is to work on their demystifier quotient which is the ability to bring their stories to life and translate these complex topics into an engaging and comprehensible story for the general audience.
Dr. Rogers is a leader in his technical field of data science and artificial intelligence (AI) in healthcare and he is also a master communicator and translator of complex topics. He is an extraordinary demystifier in his area of expertise and he is currently the Expert in Residence for AI at UCSF Smarter Health where he is developing FDA-cleared AI to improve healthcare, and he is also an advisory board member at the Institute for Applied Computational Science at Harvard University where he’s currently helping shape the Data Science, Computational Science, and Engineering Graduate Programs at the Harvard School of Engineering and Applied Sciences.
Dr. Rogers is the co-founder of Orchestrated Intelligence which focuses on AI to augment supply chain planners. He previously served as Chief Data Scientist for IT Transformation in the Data Center Group at Intel, and as Intel’s Chief Data Scientist for Analytics and AI solutions. Prior to his work at Intel, Dr. Rogers had an impressive array of leadership experiences through founding and co-founding startups in the data science field.
Dr. Rogers earned his Ph.D. in physics from Harvard University and B.S. in Physics from Berkeley.
What You’ll Hear On This Episode of When Science Speaks
[01:07] Mark introduces his guest, Dr. Bob Rogers
[04:03] Tips on how to tell a compelling story about your work
[06:50] Is communicating through vivid and simple terms in order to reach more people consider as a dumbing down of concepts?
[08:47] Why scientist and engineers struggle to translate high-level concepts in a way resonates with the general audiences and policymakers
[13:21] Dr. Rogers shares his perspective on the capabilities of AI now and in the future
[16:29] The challenges and risks associated with the wide adoption of AI
[20:48] Dr. Rogers recalls his project at the Center for Missing and Exploited Children and how he used AI to improve their data analysis and other processes
[30:16] The keys to becoming an effective data scientists
[35:38] How PhDs and postdocs can use their knowledge in entrepreneurship in a meaningful manner
Connect with Dr. Bob Rogers
Understanding the process of better communicating your work
The value of breaking down high-level concepts into a narrative that the general public can understand is an important factor to consider in the field of STEM. However, it is a skill that remains elusive for many scientists and engineers because turning technical research into a compelling story isn’t the easiest thing to do. But Dr. Bob Rogers says that it’s possible if you start by understanding the needs of your audience and answering these questions: why they’re there, what they need to know, and what can your product do for them.
Once you have those dialed in, it will be much easier to communicate with them in an effective and engaging manner that will allow them to resonate with the work that you have done. By simplifying the terms you use and sharing your narrative in a compelling yet easy to grasp manner, you have already made it that much easier to get your message across. It is about knowing every detail about the topic at hand and finding a balance of what to add or leave out in crafting a narrative from a complex topic in order to make it comprehensible for your target audience.
Leveraging AI now and in the future
Artificial Intelligence is a system that’s built to answer a very specific question. If you think about AI that way, then you’re well on your way to being able to maximize it to its full potential. AI shouldn’t be viewed as a competitor for human skills; rather, consider it as a source of support that improves the processes and output that’s gathered from large amounts of data.
However, there are risks and challenges involved when in the adoption of AI, with the biggest one being its inability to recognize underlying bias in the data that’s entered within its system. This is particularly true with the extant privacy laws for data protection across various industries.
Learn more about Dr. Bob Rogers, his expertise, and his work on this week’s episode of When Science Speaks.
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