Date
17 January 2019
Artificial intelligence relies on the effective accumulation and efficient processing of big data. Photo: Bloomberg
Artificial intelligence relies on the effective accumulation and efficient processing of big data. Photo: Bloomberg

We are really just beginning to understand AI

The Institute of Big Data Governance was formally established last week. A number of industry players and organizations have joined the institute including Alibaba, AWS, Bank of China, Cyberport, EY, Google, Hong Kong Science and Technology Parks Corp., and Google.

It will operate as a non-profit, neutral and open forum for promoting good data governance among big data users, regulators, governments and institutions across Hong Kong to help build the city into a global data hub.

Data security is becoming an increasingly important issue as more and more companies seek to integrate big data into their daily operations.

Data governance has been in existence since 1980s. It has been redefined with the advent of the internet, mobile network, cloud computing and big data.

It is becoming more difficult to ensure data security and quality because of the huge volume of data involved, plus its non-structural and diversified nature. 

With the growing number and frequency of data leaks, as reported in news media, more and more companies are becoming aware of the importance of big data governance.

Artificial intelligence may generate unexpected outcomes – or even cause harm – when data quality is poor.

In fact, humans are just beginning to understand AI. Likewise, our knowledge of big data, AI’s key input, is still limited.

Big data governance is constantly evolving. I believe the future approach would be very different from what it is now.

The late Zhang Shoucheng, a well-respected physicist, said the history of aviation started when humans began mimicking birds. 

“When humans saw birds fly, we wanted to imitate them, and the first thing we did was to tie wings to our arms. Eventually, we discovered aerodynamics, which led to a real breakthrough. Today, we have great airplanes that fly high and fast, but they do not look like birds at all. 

“Current AI is simply copying the way human neurons work, but we should think more of the fundamental mechanism. When we truly want to find out the mathematical theory behind, there would be a huge leapfrog of AI.”

This article appeared in the Hong Kong Economic Journal on Dec 11

Translation by Julie Zhu

[Chinese version 中文版]

– Contact us at[email protected]

RT/CG

Venture Partner of Sequoia Capital China, former head of the data committee and vice president at Alibaba Group.

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