7 TED Talks for Students of Data and Information Science
Over the last 15 years, the emergence of Big Data has been perhaps the single largest change in how business is done. In the early years, companies grappled with the basic infrastructure they would need to capture and correlate data. They confronted problems such as bandwidth, security, and the underlying difficulty of respecting users’ basic rights while performing extensive data collection. Now however, those basic systems have matured and Big Data is a reality.
Today’s data scientists, analysts and business decision-makers face even greater challenges. They are called upon to not only simply collect and categorize data, but to make inferences about what it all really means. The problem-solving approaches developed today could have a vast impact on the future direction of technology and, indeed, society. These seven TED Talks help put those challenges, possible solutions and potential outcomes into perspective.
1) Susan Etlinger: “What Do We Do With All This Big Data?”
The question of what exactly to do with data is a problem that has stood out for more than a decade now. Data are arriving at a greater velocity, and from a greater number of sources, than ever before. However, truly ‘operationalizing’ it at the corporate or individual level is still a challenging process. Even highly informed decision-makers can misunderstand data and apply their biases to it. Susan Etlinger, a leading data analyst with Altimeter Group, urges a reassessment of how we truly make meaning from data sets.
2) Kenneth Cukier: “Bigger Data is Better Data”
Now that the Big Data transformation is truly underway, data will always be growing — never shrinking. This places enormous responsibility upon data analysts, of course, but also opens the door to technological advances that were unthinkable as little as a decade ago. Beginning with the example of self-driving cars, Kenneth Cukier — Data Editor of the venerable Economist — connects the dots to understand how Big Data will drive continued technological change. The intersection between Big Data and machine learning may produce unexpected benefits.
3) David McCandless: “The Beauty of Data Visualization”
For data to be of value to ordinary individuals, it must be visualized in some form. When data are visualized effectively, it becomes easier to process and act on. Even the most complex data — such as that involving military spending — can be transmuted into a new format. This allows people to make more intuitive and effective decisions. But, as data journalist David McCandless shows, the benefits do not end there. By using the power of visualization, data can indeed become beautiful.
4) Jennifer Golbeck: “The Curly Fry Conundrum”
Billions of people all over the world spend time engaging in social media every day. During this time, they might do all kinds of things online they don’t think twice about. It can be likened to mindlessly eating curly fries. Through the power of Big Data however, businesses derive a tremendous amount of information from even the most innocuous online behavior. In this talk, computer scientist Jennifer Golbeck draws back the curtain to demonstrate the power of these data points.
5) Deb Roy: “The Birth of a Word”
Deb Roy is an MIT researcher who focuses on cognitive science, particularly big questions on how children learn languages. To bring his understanding to the next level— and develop new insights that might aid in language learning for machines — he recorded 90,000 hours of footage chronicling every aspect of his infant son’s life. This talk is the result of searching that footage, more than 3,750 days’ worth, and synthesizing his findings into less than 20 minutes.
6) Glenn Greenwald: “Why Privacy Matters”
In the wake of Edward Snowden’s revelations on the scope of U.S. government surveillance, former Guardian columnist Glenn Greenwald became one of the most controversial figures in the mainstream media. This TED talk comes from Greenwald’s years of tireless work analyzing, commenting on and publicizing those revelations. In it, he advocates for the idea that privacy matters to everyone, even if you are not doing anything wrong.
7) Mallory Soldner: “Your Company’s Data Could Help World Hunger”
Business often focuses on the ways Big Data can be monetized. Cutting costs or improving sales are the end goals for the vast majority of commercial forays into Big Data. However, that data is so foundational to the people and experiences it describes, that it could be used for much greater purposes. Self-described ‘data activist’ Mallory Soldner puts this into perspective. Her talk shows how data collected by corporations can be applied to make powerful, lasting changes to long-standing humanitarian issues — often much more quickly than anyone would expect.
Data science is not about data alone, but about how we conceptualize data to make it an effective decision-making tool. Even experienced, educated data scientists must be careful not to take logical ‘shortcuts’ —actions that can make data seem intuitive while obscuring deeper and more significant meanings. This may become the central challenge of data science in coming years.
As with any type of scientific researcher, data scientists must be prepared to challenge their own preconceptions and to take ethical responsibility for the implications of their work. For no matter what new technologies, business models or paradigms come from Big Data, they stand to change the world in ways few other advances have in the past. These talks will help data science experts see and embrace the broader philosophical imperatives of their remarkable role.
Information means more than knowledge, it means solutions. When technology, people and information intersect, society and industry benefit. You can harness the power of information with our online Master of Information degree at Rutgers University.