Big data requires big visions for big change | Martin Hilbert | TEDxUCL

This talk was given at a local TEDx event, produced independently of the TED Conferences. Will data scientists dominate the world in future? While this seems to be an omnipresent conclusion nowadays, it will certainly not be the case. Data are based on what happened in the past, which restricts our forecasting ability to futures similar to the past. But most public and private sector activities aim at creating futures distinct from the past: hopefully ‘a better world’. Making predictions about unprecedented futures requires more than data, it requires theory-driven models that envision futures that do not exist in data. Fortunately, digital tools also assist us in envisioning futures that have never been.
At the University of California, Davis, Martin thinks about the fundamental theories of how digitization affects society.
During his 15 years at the United Nations Secretariat, Martin assisted governments to take advantage of the digital revolution. When the ‘big data’ age arrived, his research was the first to quantify the historical growth of how much technologically mediated information there actually is in the world. He is convinced that ‘big data’ is a huge opportunity for making the world a better place. After joining the faculty of the University of California, Davis, he had more time to think more deeply about the theoretical underpinning and fundamental limitations of the ‘big data’ revolution. When TEDxUCL asked him if there is a limit to the power of data, he answered with the fundamental limitation to all empirical science. The fundamental limit of ‘big data’ has to do with social change and how we envision the future. Luckily, the digital age also provides solutions for fine-tuning our future visions. Martin holds doctorates in Economics and Social Sciences, and in Communication, and has provided hands-on technical assistance to Presidents, government experts, legislators, diplomats, NGOs, and companies in over 20 countries. More www.martinhilbert.net
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[@gdoroja]

Right on the button, Martin! Thanks for demystifying the big data hype ☺. Use the past to create a better future rather than more of the past using big data analytics.

[@m.morshedloo]

Amazing lecture professor Hilbert. Thank you

[@annapolitica9490]

My favourite teacher that’s for sure!

[@ratjellybastard]

Thank you for this talk. This put together a few important pieces for me as I watch people get "locked in" to thought- and behavioral patterns; where career trajectories seem more and more like defiles through which we must march towards a long and looming future, as I watch some of my generation mourn a political past of which our present is a mere shadow, and as I learn about search and hiring practices that organizations are implementing that are based not on the goodwill or determination of individuals, but on their credentials and psychometric evaluations of their implicit biases and tendencies, as I watch people get kicked out of networks, careers, platforms, access to credit, housing opportunities, for the faults of their pasts; as I watch my culture ossifying, becoming sclerotic, suspicious of vision, seemingly suspicious of and contemptuous of life itself, indexing instead a Platonic heuristic for people, objects, and narratives of which those same elements of the Real are only ever an imperfect instance.

[@janrad131]

Enjoyed good info

[@hazeljoycrizaldo8330]

Dr. Martin Hilbert talks about using theory for social research to establish more reliability in the results, formulating hypothesis that can be tested and drafting a framework that has basis in theory, leading to results that can be cross-checked, and ultimately, conclusion that is more scientifically accepted. With this use of theory in social research, he encourages Social Science to be an established and recognized discipline. I think it is alright to venture in Social Science researches if the study's goal necessitates the use of quantitative methodology, especially if it is about Knowledge Management and Information Communication Technology. The nature of study calls for such type of research and methodology. Also, if data analytics and knowledge should be used to forecast the future, it calls for a strong fundamental theory that can establish well the projections or hypothesis and lead to more data sets that can be verified, and the conclusion will be well accepted by the scientific community.

[@muhibbdeen2]

Thanks so much, verily, most big data are even sometimes altered to suite situations in the real world.

[@SystemsInnovationNetwork]

"So is there a limit to the power of [big] data, clearly yes we will surely need data to calibrate our models, to inform our visions, to ground our visions into reality, but data is from the past and our past shall not define our future, our visions define our future, and visions, paradigm changing theories, and out of the data box thinking, is what is needed more than ever to keep the course toward a different, a better future, especially in a big data world"

[@artcurious807]

Complexity Labs yes there is a limit, because data can be inconclusive, it can be corrupted, it can even be false. What if the rise in temperature and CO2 is caused by volcanos or jet travel? Or, Imagine in a court room the FBI charges you with drug smuggling. They can fake your IP address, they can photoshop your image, they can use AI to falsify your voice, they can place drugs in your community, spread false rumors. All of this can be used as data to draw false conclusions. Data must be verified and correlate with real sources. Whether it’s climate models or crime statistics it must analyzed by humans and the conclusions about the future should always have a caveat.

[@shiro_seraphim]

We must all remember that big data can NOT ONLY point to the problems of our society, but it CAN ALSO point to the solutions.

[@TheNigome]

I'm agreed but 95% of people rejected to change. Best example is that paper consumption haven't decrease since 2007 year were smartphones went out in the market. Most of the people hate to change

[@DAWN001]

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