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How massive data growth is good for Artificial Intelligence (as well as a problem)

Posted in Online on 7th Jul, 2017 04:35 PM by Alex Muller

Ninety percent of all the data available online today has accumulated over the last couple of years. This pool of data is projected to grow exponentially as we all contribute to it each day through 500 million tweets, 4.3 billion Facebook posts, 5.75 billion “likes,” and 6 billion daily Google searches.


The Ridacati Group reports that 205 billion emails were sent each day in 2015, and it estimates that by 2019 that number will increase 20 percent to reach 246 billion emails.

This data growth is inextricably linked to the development of AI. Deep learning models have become routine in almost every area that deals with data. And the more data AI uses, the smarter its algorithms become, allowing it to deliver insights we never could have imagined.
The rapid spread of smartphones in emerging markets is another factor that will impact the growth of data in the future. Ericsson predicts that regions like the Asia Pacific, the Middle East, and Africa will account for 80 percent of all new subscriptions in the next five years, with 6.1 billion global smartphone users by 2020. Another very significant growth factor is the development of the Internet of Things (IoT) market. According to Gartner, the global number of IoT devices that are connected to the internet will exceed 20 billion by 2020.
Such astonishing digital growth presents two major challenges that need to be addressed: proper data management and data protection.
Experts claim that 76 percent of all organizations are planning to increase or maintain their investment in big data over the next two to three years. This number supports KPMG’s survey, which states that 99 percent of C-level executives said analysis of big data was important to their strategy. The study concludes, “Today, the issue is no longer about owning the most data but rather … how to turn data into insights.”
It’s easy to see that humans are incapable of processing terabytes of exponentially growing data, and only the application of AI technologies can turn disorganized mounds of data into “knowledge discovery,” through logical classification, clustering, and knowledge graphs.
Several companies are now trying to find the AI “Holy Grail” that will allow them to turn raw data into valuable knowledge. Some are developing NLP (natural language processing) technology to facilitate human-like conversations between a user and a platform. Take the following scenario between AI and a user:  “Find a meeting recap from last month and send it to the marketing director. Also, find my diabetes records for the last three months and send them to the doctor.”
The AI personal assistant will search for this data and send it to the requested recipient. If you don’t really care about the confidentiality of your medical records, you don’t need to worry about a third party gaining access to your information. But very few people are unconcerned about their data security.
This example highlights the necessity of proper data security products, especially when it comes to sensitive data, like health and finance records. As a survey by privacy company AnchorFree shows, 84 percent of people are “more concerned with privacy today than they were a year ago.” And a recent FCC initiative that allows internet providers to sell browsing history doesn’t inspire much hope that personal data will be protected by the government.
All of this means users need to take control of their personal data and take actions to protect the sensitive information that they are not willing to share.
As companies enable users to tap into the convenience of AI, it will be important that they give users the ability to protect the data that is most valuable to them. We believe convenience and privacy can coexist for users (in the consumer and business markets) and that companies can give users the ability to strengthen privacy options based on their needs.
It all comes down to giving the user greater control over their own data. For example, you may be willing to allow your refrigerator to send data to your local store letting it know that you are out of milk so the store can automatically deliver more milk. However, you may not be comfortable with websites collecting search and browsing history related to your health, finances, and family, and you may use privacy products to ensure that such data is protected.
In the not-so-distant future, AI powered by big data and online privacy will become multi-billion dollar industries with the potential to impact billions of people. This is why we have witnessed a record investment in both AI and security sectors over the last five years. This interest will only continue to expand as the need for such services grows.

Tags: robotroboticsbusinesshardwaresoftwareAI

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Author: Guest
Posted: 2017-07-08
Indeed, investment in AI and in data protection has been huge. However, both remain at a stage when further development is required to meet the needs
1 Replies
Author: Guest
Posted: 2017-07-08
I agree. Big data need big protection and options for privacy to support further developments in AI that is becoming more and more accessible Reply


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