You’ll be familiar with the concept that data is now the world’s most valuable resource.
And by 2020, there will be 44 zettabytes of data in existence – which, according to the World Economic Forum, means there will be 40 times more bytes than stars in the universe.
The discipline which is distilling this information to unlock its dynamic power for humanity is Data Science – here are five ways it’s changing the world.
1. Speaking your mind
US academics funded by Facebook Reality Labs have built a brain-computer interface which can precisely decode words and phrases from brain signals in real time.
Electrodes implanted in the brains of volunteer patients receiving treatment for epilepsy recorded brain activity while they listened to a set of recorded questions and responded out loud. Then, the data generated was fed into machine learning algorithms which were eventually able to use brain activity alone to decide whether a patient was speaking or listening and to then work out exactly what was being said.
The team hopes that in the future, building biomedical devices with larger vocabularies will allow patients who have suffered strokes or spinal cord injuries to communicate naturally.
2. Data-driven storytelling
Stories have helped humans make sense of the world and predict the outcomes of important decisions since the very first societies were formed.
And corporate publishing houses have capitalised on our insatiable appetite for relatable stories by serving them up as bestsellers – but whether a book ever makes it to print is dependent on the writer having the right connections as well as the required talent.
However, storytelling platforms like Wattpad are democratising publishing with machine learning algorithms that analyse grammar, vocabulary and user engagement to provide data-driven insights to reveal which of the 500 million titles uploaded by its community of 70 million readers and writers are most likely to connect with an audience.
3. Supercharged food production
The CGIAR (Consultative Group on International Agricultural Research) is a global partnership of organisations dedicated to a food-secure future.
And its Platform for Big Data in Agriculture actively promotes the many ways in which Data Science can supercharge food production and meet complex challenges posed by population growth and climate change.
For instance, feeding granular data from satellites, telecoms networks, sensors, drones and smartphones into predictive analytic algorithms and making datasets open and shareable would empower farmers worldwide with the most accurate information on everything from optimising soil nutrients to combatting crop diseases.
4. Ecology SOS
With its Science on a Sphere (SOS) data display system, the US-based NOAA (National Oceanic and Administrative Administration) has been helping students and museum visitors visualise concepts like Earth’s weather patterns and Saturn’s rings with eye-popping room-sized spherical projections.
And now, the SOS Explorer app means you can download the same system to your phone – effectively placing 500 powerful human, elemental and interplanetary datasets in your pocket.
These types of applications are a timely reminder that Data Science is an amazing educational tool which will prove invaluable for inspiring the next generation of scientists.
5. Life on Mars (and elsewhere)
Biofilms are some of the oldest forms of life anywhere. They’re congealed collections of bacteria that grow on everything exposed to moisture and leave behind distinctive textures on materials like rocks – strong indicators that some life-form has been present.
With this biological footprint in mind, NASA scientists are now teaching algorithms to identify life on the Moon, Mars and on future missions to Jupiter’s moon Europa.
AI-powered data imaging and analysis tools attached to rover vehicles will decide in real time which rock and soil samples are worth collecting, by identifying whether they have the biofabrics or textures that indicate the presence of biofilms and water.
If these five fascinating developments are merely the tip of the Data Science iceberg, the future breadth and depth of this field might prove to be boundless.
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