The Future of Solving Complex Problems: How Smart Data Can Save the World
This event took place at Social Media Week in New York. You can get the SMW Insider Digital Subscription to access the full video of this event and 60+ other #SMWNYC sessions.
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In an attempt to figure out how we can do more to change the world, Social Media Week brought five leading thinkers in the data and analytics field to discuss some of the big questions surrounding data’s impact on social change.
Brian Reich, Director, Hive/USA for UNHCR, led a session on why we aren’t doing more with data analytics and science to discover solutions for social good, and what some of the barriers are to doing this.
Panelists included Christine Campigotto (Social Sector Lead, Civis Analytics), Matthew Daniels (Creator, Polygraph), Ari Wallach (CEO, FastCompany Futures), and Mike Williams (Research engineer, Fast Forward Labs).
“Can we solve the world’s more complex problems with big data?” Ari Wallach sums the answer up saying, “desire is there, but the ability to access it across platforms is not there.” Another valid point was voiced from Mike Williams, adding that part of the problem therein lies in getting the human capital (the data scientists) to the table, since the money is elsewhere.
This poses a strong argument that was echoed by others throughout the talk, this idea of getting the best people, those at the top of their fields, to do the right thing with their skills. While this may be a valid reason as to what’s stoping us from solving the big problems, it illuminates an important idea about the altruistic nature of each of us.
Christine Camigotto spoke to this bigger philosophical component of the question, “The unit of measure is a human, and we know that humans don’t always behave rationally.”
If we all assume that someone else will do it, what happens when no one does? There’s no allusion of the truth here, most of us are out for ourselves, but if none of us are mining the solutions to social issues and creating social good for us collectively, who will? How can we change the world if we don’t help?
Data allows us to capture valuable insights, mine and measure information that can aid in changing the entire landscape of a business or cause. The power of data is not lost on any of us who work with social media or with data science.
The speakers also discussed if the same data scientists that can measure and catalog the information, can also be the same people to ask the right questions to solve the problems. Because isn’t the most important component of data analysis, asking the right questions?
While many of the panelists argued that the data is not there- whether non-existent or non-accessible, I would side with Matt Daniels in saying that not enough of us are interested in asking the questions, right or wrong. Matt said, “data is not as big as it sounds, and focus the conversation less on data and more on how do we solve this, based on the info we have.”
I believe we can agree that the future of marketing largely lies within predictive analytics, therefore the role of predictive analytics in the data conversation should be considered. Ari Wallach, Founder of Fast Company Futures, brought up a good point in the data conversation.
He points out the objectivity or lack thereof, in the potential outcomes of predictive data. “Predictive data is not a purely objective data source, we are looking at how people have behaved. It’s almost like we are self fulfilling that prophecy” And goes on to say, “how do you overcome the historical bias in the way you present it so that you are not having the same conversation, so we can get to where we want to be ?”
Lastly, one of my favorite ideas offered up references the importance in utilizing the knowledge seeded from data analytics to help the entire organization, not just one department.
Furthermore, the importance of spreading the power of data across the organization will be able to offer a better system, Ari says we will need to “stop holding onto a centralized system of power, and understand that it will inevitably flatten the organization in a social good sense.”
Christine Camigotto followed, echoing a similar sentiment, saying we must “stop believing that data science can only exist in there, it’s every level of the organization even of it.”
We do not need to remind ourselves how powerful data is, because most of us have personally seen the benefits and continue them to our advantages. But clearly we need to do our part in asking what we can do to be better citizens, to improve our world, to be socially conscious with our skill sets to help work towards the solution for this problem.
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