TEMPO.CO, Jakarta – THE most valuable resource around now is actually no longer oil or any other natural sources, but rather data. Indonesian companies, the government, and the public ought to realize that.
In the midst of this digital-based industrial revolution, every business opportunity can now be detected and predicted through processing information on trends, consumer behavior and profiles, as well as from a range of other data, often referred to as ¡®big data¡¯. The availability of, and opportunities to make, profits can even be created through its accurate analysis.
Big data is not just statistics. It is a range of data and behaviors collected from Internet users, accessed from computers or smartphones. Whenever someone accesses a Google or Waze map, Google’s smart machines will record that user’s habits: where they are going to, when they go, and other information. It is not surprising, then, that Google and Waze maps can estimate which roads have very heavy traffic or not. Whenever someone surfs in cyberspace, Facebook and Google’s big data engines record the sites they frequently visit, the news they like, and their favorite holiday destinations.
Whenever someone uses the Go-Jek application, for example, that company’s big data engine records information so it can then predict what snacks in a particular area-for instance South Jakarta-are most ordered at weekends, say martabak or fried bananas. If Go-Jek wants to, it could also estimate the increased demand for flour and margarine for martabaks every weekend.
Scary? Hold on: consider all the big data Facebook has. Facebook Indonesia, with its 115 million users in 2017, may well have more complete data about those users than the Ministry of Home Affairs. It knows where someone went to school, where they work, their mobile phone number, and even their political affiliations just from analyzing the news often shared on their Facebook pages.
We need not then be surprised if the expansion of industry titans like Alphabet (the parent company of Google), Facebook, Microsoft, and Alibaba appear to be unstoppable. They are able to read trends in consumers’ needs, then either form a new company or acquire one to meet those needs. This is what convinced Alibaba.com website founder Jack Ma that the data business will be the biggest one in future. His company expanded into Indonesia through the many businesses now utilizing big data here, such as Indonesia’s top online shopping sites Lazada and Tokopedia. Indonesian companies must not get left behind in adopting this technology. There are 132 million active Internet users in Indonesia.
It is very important that the government is not too hasty in regulating the use of big data. It should not just arbitrarily prohibit it, as it did with regulating online taxis. It is enough for the government to remain as a referee of the business players.
Companies’ use of big data must also be done with respect for the rights of their customers. Consumers’ privacy should not be abused. Apple Inc demonstrated its dedication to this: the US-based company refused requests from the Federal Bureau of Investigation (FBI) in 2016 to access Apple’s data of users the Bureau considered had violated the law.
The public, too, must be aware that all their activities are recorded in big data. This is the price we must pay for convenience in this digital industrial revolution era. All our information and activities are recorded whenever we use Internet-based gadgets. Welcome to the big data era, and welcome to the information tsunami.
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Fitness tracking app Strava wanted to show how people use its app all over the world.
In November, it created an interactive heat map that displayed one billion activity data points — like running and cycling — made public by users.
But over the weekend, observers noticed that Strava’s map may have inadvertently revealed sensitive U.S. military locations and personnel at bases in countries around the world.
The controversy around Strava demonstrates a common issue with the relationship between tech companies and their users: People casually using an app often don’t understand what companies do with their data or how to properly protect it.
“Before people can even have a basic level of protection of some kinds of data, they have to wade through these lengthy privacy policies, or find the setting, or even have some awareness that potentially sensitive information is going to get out there,” said Michelle De Mooy, director of the Privacy & Data project at the Center for Democracy and Technology.
Strava has three levels of privacy in its app: Users can treat it like Twitter and publicly share their activity data for anyone to see; they can choose to let only certain people see their activity; or they can make their activity completely private. The default option is to share personal activity data publicly.
In a November blog post announcing the heat map, Strava data engineer Drew Robb said the company respected privacy rules when it created the map and only published public data. Strava did not respond to specific questions about user data, but said in a statement earlier Monday it is “committed to helping people better understand our settings to give them control over what they share.”
Tech firms revealing user data without anticipating the consequences is not uncommon. Companies assume it may be interesting to reveal user statistics, but receive backlash when people feel uncomfortable with the information exposed.
“What they fail to understand is that data represents people and people’s preferences,” De Mooy said. “Every tech platform is dealing with this unintended consequences problem, and it’s partly because of the misalignment between expectation and intention, and what they’re doing.”
Related: US military reviewing security practices after fitness app reveals sensitive info
In December, Netflix tweeted a joke about 53 people who watched its holiday film “A Christmas Prince” once a day for 18 days. Some people criticized the tweet as inconsiderate. The tweet also reminded users that the video streaming company has massive amounts of data on people it could access at any time for any reason — including poking fun at them.
In 2014, Jawbone — a now-defunct fitness tracker — published users’ sleep data following an earthquake in Northern California. People saw their anonymized personal information become a data point in a major public event, and some felt uncomfortable when data collected in their bedrooms became part of a study looking at sleep data during the natural disaster.
In 2011, Fitbit exposed the self-reported sexual activity data of some users through profiles that were public by default. Fitbit changed its sharing options after the incident to make a private profile the default.
Many apps also sell personal data to third-party companies. This practice is common, though the general public is often unaware of their app’s policies regarding data brokering. These types of sales are legal if disclosed, but users might not see the disclosures in lengthy privacy statements.
The U.S. Central Command said it is looking into refining its smartphone and wearable device policies following the Strava revelations.
White House cybersecurity coordinator Rob Joyce tweeted on Monday that the Strava heat map highlights the risks of big data analytics.
“It goes well beyond fitness trackers. Security and OPSEC need to be considered in our new reality,” he said in a tweet. “While policy evolution is needed, it is important to make good security policy balanced by not over reacting too.”
People who are concerned about privacy should read apps’ privacy policies and check the types of information that apps ask to collect, including permissions regarding a phone or tablet’s camera, calendar and contact list. Social apps are often public by default, De Mooy said, and people must manually change their settings to be private.
“If you are a person with sensitive information — whether that is your immigration status, gender, politics, or sexual orientation — you may want to consider that once you’re using a bunch of different apps, that information is probably getting compiled about you,” De Mooy said.
The insane rate of growth in data has resulted in enormous amounts of data sets for organisations. In order to meet the present day needs of real-time business outcomes, meaningful analytics are the key differentiator to smarter decision-making and gaining competitive advantage in the market.
Data is dynamic, distributed and diverse
Transformation is happening all across the industry, shifting from equipment focused power in the industrial age, to today, where data holds all the trump cards. Organisations now need to both innovate on and safeguard critical data of employees, customers and business partners. In the era of Big Data and globalised open innovation, this is both a challenge and an opportunity with data generated every day at an exponential rate.
The truth is that data has gone beyond staying behind the firewalls of devices. Data patterns are now enabling a viable, robust and thriving e-commerce environment by reducing application response time. Disruption is the name of the game, and a dynamic and efficient use of data chooses the victor.
When we talk about AI and data privacy, we are essentially referring to machine learning implemented on Big Data, also commonly called Big Data Analytics. Big Data Analytics has a lot of positive real-world effects. A most common example is the data generated in the transportation sector that can be used to reveal travel patterns across road networks. By identifying such patterns, services can be created to benefit travelers.
This data is what causes a concern because as individuals, we are not sure what is private and what isn’t today. In fact, a lot of this data is stored in the hybrid cloud. This means that data is forever moving. The secure movement of this data, which could be living in a public cloud or on a secure server, is critical.
Privacy by design: Breaking down the hype
Privacy by design is a policy framework through which privacy is proactively embedded into the design and operations of the IT systems, networked infrastructure and business practices. The root principle is based on ‘enabling service without data control transfer from the citizen (user) to the system’. A good example is GPS, which gives a location without giving away the identity of the user.
From a compliance standpoint, as an example, privacy by design is a new part of European Union regulations, contained in the GDPR or General Data Protection Regulation (that comes into force in May 2018) as well as the recent urge to adopt the ‘privacy by design’ framework when ‘right to privacy’ was elevated to a fundamental right under the Indian constitution. The concept was also in the news back in 2010, when over 120 different countries agreed that they should contemplate privacy in the build.
It is true that new businesses will face challenges with enormous amounts of data-streams, while looking for patterns that open up new business opportunities. What is required is the adoption of a comprehensive approach to data protection, which helps balance the need for data access with the need to protect that data from attackers. Companies deploying AI are well aware that the future success of this technology lies in ensuring security without a trust deficit.
How AI and privacy can co-exist
The need of the hour is to embed a framework of data privacy and data protection policies right at the source—into Big Data analysis so society as a whole can benefit from Big Data and AI without privacy concerns.
Data privacy encryption solutions keep private data private and help AI proponents meet regulatory compliance security mandates. For example, our data security solutions offer encryption without traditional compromises around performance, OS-dependence, and ease of use, and enable corporations to meet compliance security mandates contained in regulations such as the Payment Card Industry Data Security Standard (PCI DSS), HIPAA or such. External regulations and internal best practices point to data encryption as a key solution to data privacy. In the end, data integrity through integrated antivirus technology, cyber analytics, standardised encryption and centralised key management, will be the ultimate succour to ensure confidentiality for data at-rest or in-flight.
The writer is VP – Data Technologies & Fabric Enablement Group, NetApp India
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Experts have warned that Hong Kong could slip behind in the use of big data. The challenge requires data sharing across government departments, so they can compare information and assess correlations for Hong Kong to function better across the board. Being a smart, sustainable city is all about maximising efficiency by saving as well as sharing resources.
Managing a city in the age of the internet of things requires governments to have the relevant data in the first place. In some cases, authorities have the data because essential services, such as electricity, water and transport, are provided by the public sector.
There are cases where all or some of those services are in private hands. Unless there are arrangements whereby private operators are required to provide the data to the authorities, accessing it is not easy.
In Hong Kong, electricity data belongs to private companies as power generation and supply are in private hands. While the electricity companies provide excellent services at a reasonable cost to users, they are not obliged to share all their data with the government. Now that energy saving has become a major part of the city’s climate-change efforts and creating a smart city is another policy objective, not having the data is an obvious hindrance.
The new schemes of control reached last year for the two electricity companies are more data transparent than before but there is room for improvement. Data for individual buildings would enable the government to draft sharper policies and help occupants be more energy efficient.
This contrasts with freshwater supply, which is provided by the Water Supplies Department, where the government has the full range of data to consider what it can do to save water. While it uses technology to identify leaks and get public water pipes fixed quickly, the department only stepped up dealing with private water pipe leaks after a highly critical Ombudsman report in 2015.
Another problem is the inability to raise water tariffs. The government is fully aware Hong Kong’s cheap water encourages wastage but fears legislators will object to any increase. So, the challenge in this case has not been the lack of data for analysis but the lack of will to deal with problems.
Mobility data presents other challenges. While the government is the largest shareholder of the MTR Corporation and can presumably access the data it needs, this is not the case for all other trips. Buses, minibuses, taxis and ferries are all operated by private companies. Small providers, such as minibus owners, may only collect minimal data.
Private companies providing public services say they can’t share data because of privacy issues or because it is commercially privileged information. In the case of water supplies, no one has complained about the government knowing how much water users consume or indeed waste. It is hard for the energy companies to make a case on privacy grounds. As regards whether releasing the data would lead to unfair competition between the two electricity providers, there could be arrangements whereby the full data could be given to the government on a confidential basis, which the government could then release publicly in a form that avoids unfair competition.
Transport data is mostly anonymous, although new services such as Uber don’t want anyone to access their personal ride histories. Even here, the companies can provide data without showing details about riders.
Data is king and it is a major policy issue for the government to work out with the private sector.
Christine Loh is chief development strategist and adjunct professor at the Hong Kong University of Science and Technology’s Division of Environment and Sustainability