Source: Data gathered from MCMC (Malaysian Communications and Multimedia Commission), Facebook, Department of Statistics Malaysia, etc.
https://www.skmm.gov.my/skmmgovmy/media/General/pdf/Internet-Users-Survey-2018.pdf
Internet
With so much information at our fingertips, we’re adding to the data stockpile every time we turn to our search engines for answers.
We conduct more than half of our web searches from a mobile phone now.
More than 3.7 billion humans use the internet (that’s a growth rate of 7.5 percent over 2016).
On average, Google now processes more than 40,000 searches EVERY second (3.5 billion searches per day)!
While 77% of searches are conducted on Google, it would be remiss not to remember other search engines are also contributing to our daily data generation. Worldwide there are 5 billion searches a day.
Innovation happens fast and slowly. The GPS applications so prevalent today to guide us from Point A to Point B took their first baby steps nearly three decades ago when President Ronald Reagan encouraged the release of military GPS signals free of charge. Will a key initiative of President Barack Obama-to move government data to the Web-lead to public benefits much faster?
Data.gov, the subject of a new HBS case study, taught for the first time this summer, highlights the potential of raw data to spur citizen creativity and practical applications. It also suggests the possibility that organizations in private industry could learn from the example of Data.gov to the extent of unlocking data from individual silos in their firm even though data remain protected within firewalls. HBS assistant professor Karim R. Lakhani, who specializes in the management of technological innovation and product development in firms and communities, co-wrote the case with former HBS professor Robert D. Austin and Yumi Yi to encourage further exploration of the benefits and tactics of open-data approaches.
“ ALL AGENCIES WILL HAVE ISSUES, OF COURSE, ABOUT MAKING DATA AVAILABLE, BECAUSE HISTORICALLY THEY MAY HAVE NOT”
Joined in class by the Chief Information Office (CIO) of the United States, Vivek Kundra, who oversees Data.gov, Lakhani led the case discussion for 50 technology executives in a weeklong HBS executive education course, Delivering Information Services. The participants-CTOs, CIOs, and other top executives representing fields as diverse as telecommunications, financial services, and pharmaceuticals, as well as government entities in the US and overseas-debated the pluses and minuses of Data.gov's decisions, its organizational realities in the context of their own experience, and tactics to improve its reach and impact. Kundra joined the conversation near the end of class to answer questions and share insights.
"There is tremendous interest internationally" in the example of Data.gov, said Lakhani. When the initiative was less than a year old it had already posted 118,000 datasets for public use. "I cowrote the case in part to provide a field guide to suggest how to encourage data openness within organizations and even countries. Some countries, I think, would be better at it: Canada, Scandinavian countries, for instance, and Western democracies generally."
Goals Of The Case Study
"I have several teaching goals," said Lakhani as he prepared for class. "One is to highlight the imperative for organizations to shift towards an open-data approach, especially in government where the default has been to keep data closed and secure.
"Second, to explore the organizational constraints and resistance to an open-data approach. All agencies will have issues, of course, about making data available, because historically they may have not.
"Third, to probe issues of strategy concerning the best way to launch a similar initiative, both in terms of technology as well as the buy-in needed from various agencies.
"Fourth, to ask executive participants in my class how Data.gov should reconcile both its public-citizen aspects of accountability and its potential to mediate private innovation.”
Success for CIO Kundra is two-fold, Lakhani added. It means fulfilling the public mission of an informed citizenry as well as also the private mission of enabling innovation. In terms of building government IT infrastructure, Data.gov demonstrates a way to be rapid and agile, not bloated and bureaucratic.
"Kundra wants to post on the site any government data that does not have national security or privacy concerns. That's a lot of data. Anything that can be put online should be put online."
Pros And Cons
In class, participants who had read the case pointed to a wealth of positive factors about Data.gov:
Transparency: Its official motive of transparency allows citizens more control of information that affects them. Giving "power to the people" puts a new set of eyes and ears on government and holds officials more accountable.
Business opportunities: Data.gov opens the door for the private sector to add value to government data. In particular, it may prove a boon to small businesses, which can devise creative applications.
Organizational agility: As a lean organization with minimal staff, Data.gov made the right move by posting, as a first step, varieties of data from the US Census Bureau, the Centers for Disease Control, the Environmental Protection Agency, and the Department of Interior, without focusing on specific "customer" needs. One executive observed, "What customers do is up to the customers.”
Changing the face of government: Its example could improve the culture of government. "Getting agencies into the habit of making data available is a good first step," said a CTO in the class. Other agencies want to look good, too. There is pressure on officials to not get left behind.
A go-to site for citizens: It centralizes datasets for citizen use. It may cut down on the volume of requests that local agencies need to field on a day-to-day basis.
Participants also probed questions of concern:
Political window dressing: Will Data.gov release controversial datasets or will it favor uncontroversial information such as health statistics over military casualties? If it releases what is construed by the public as sanitized data, will citizens view the site cynically?
Customer needs: As business people, some class participants wanted to see a clearly outlined customer perspective defining customer needs.
Tradeoffs for fast growth: Several participants wondered what the endeavor interrupted in local agencies as it began to fulfill its mandate of gathering data. "I don't believe there were no ripple effects," said one executive.
Public trust and consistency of data architecture: Does government data match across various agencies? Will inconsistencies raise doubts among the public about data veracity overall?
As instructor, Lakhani challenged the executive participants to consider Data.gov as a lean organization needing to fulfill quickly President Obama's mandate without excessive discussion of pros and cons. They would experience similar pressure from an executive directive in any industry, he said. "We have to face tradeoffs when we design and execute. There are different ways to approach the same problem," he said.
Several participants in the class agreed. Said one, who works for a government agency, "I can attest that when huge initiatives come along, whatever 'seems impossible' soon becomes a fact of life. To say, 'I need to do a study first' is not a [wise] response.”
Advice For The Us Cio
Asked by Lakhani how Data.gov should grow strategically, executive participants suggested that while transparency of government data overall was an important goal in principle, Data.gov should prioritize its acquisition efforts and pursue specific high-value targets. One CTO recommended giving priority to environmental data in order to encourage the public to invent ways to help clean up the disastrous effects of the recent oil spill in the Gulf of Mexico.
Another class participant pointed to an example of high-value data use documented in the Data.gov case study: In Virginia where there were problems with a bidding process, citizens were able to learn where exactly money was being wasted, and take action to stem the tide.
A third said that Data.gov should focus less attention on data acquisition than on encouraging private industry to develop applications. "Brand them as 'powered by Data.gov.' The end user, rather than the average citizen, should be a key focus of your strategy," he advised.
These views were challenged by one participant, however. For the sake of public trust, he said, Data.gov should focus on transparency rather than commit too much organizational attention to the development of applications. "A problem we face in the United States today is a lack of trust in government officials," he explained. "There is no point in adding services over a foundation we don't trust. The number-one priority of Data.gov should be to restore confidence in our government. The average person should be able to interpret these data.”
The Us Cio Weighs In
"This discussion has been about binary choices," observed Kundra with a smile as he rose to address the class. "I would like to step back a bit and share with you some of the motivations behind Data.gov."
Information is power, he began. By "democratizing data," ordinary citizens have the ability to shift the balance of power in positive ways that can encourage innovative ideas to be developed into practical goods and services. "Washington, DC does not have a monopoly on the best ideas," he told the executives. "The public has the ability to innovate.”
Data.gov allows people to be watchdogs as well as innovators, he continued. One helpful innovation marries government data about recalls of baby products with the nifty Red Laser app that is available for the iPhone: Before considering purchase of something for their child, parents with the app can scan the bar code of any product and immediately check for recalls, thus ensuring the safety of their children.
Releasing government data and allowing the public to innovate creates a process of continuous feedback, he said. People can see how the government spends taxpayer money. "Our goal is to create a runway, a platform for innovation. The government can't make the most innovative apps. But Data.gov can be a platform.”
“OUR GOAL IS TO CREATE A RUNWAY, A PLATFORM FOR INNOVATION”
Transparency of information leads by necessity to controversy, Kundra allowed. People are bound to ask which data is on the site and which is not. "We release data on toxicity, but not on national security and privacy. It would be a mistake, for instance, to release zip-code level data about health care" because the privacy of individuals would be at stake, he said. Data.gov is seeking even more raw data from US agencies such as the Department of Defense, Health and Human Services, and the Environmental Protection Agency, but his organization does not expect to gain controversial datasets.
Rather than focusing unduly on issues of data governance, the executive participants should think about innovation opportunities in data curation, he suggested. "Some US government data is still on COBOL-based platforms," Kundra reminded the class. "So we think an industry will form around data curation. The Internal Revenue Service, the Centers of Disease Control, and the National Institutes of Health are huge enterprises. There will not be a single governance model.”
What Can Private Industry Learn From Government?
Data.gov serves as a beacon for changing the IT culture in Washington, DC to focus more attention on execution, he said. As CIO of the United States, his role from President Obama is to identify troubled projects, hold CIOs accountable (there are 200 CIOs across various government agencies, he said) and practice relentless follow-up. Gone are the days of deliverables scheduled five to ten years from now, Kundra promised. "A deliverable that is customer-facing should be ready within 6 months. On Data.gov we put up our IT Dashboard, an interactive site that tracks Federal IT investments over time, in 60 days.”
A key aspect of the Data.gov case is the extent to which innovation can be encouraged within individual organizations by pursuing a similar model of openness of data, added Lakhani. Just as there are benefits for the public when data is unleashed, so are there benefits for innovation-minded employees in private enterprise when data that was formerly held within silos is made available throughout the organization.
"CIOs and CEOs could consider what data they should make available throughout their enterprise," Lakhani said. "It would be great if any employee could look at data and think about different ways to mash it up. Just as there are concerns about security and privacy with the government's data, there are security, privacy, and intellectual property concerns about private-sector data. But Data.gov shows that those things are manageable."
How do countries’ strategies compare? And what are the implications for the world? I have selected six countries with very different approaches which will have a significant impact outside their national boundaries.
US
Distinctive characteristic Defend the lead; private sector the envy of the world
State role Largely silent Highlights
Clear lead in AI in terms of leading-edge research, advanced algorithms, specialised computing hardware, fast-growing inventory of data and talent. Tech giants such as Google, Amazon, Facebook and Apple are investing billions in AI R&D.
No central AI policy, but government agencies such as the Defense Advanced Research Projects Agency (DARPA) and the Intelligence Advanced Research Projects Activity (IARPA) are funding AI projects. DARPA, which is responsible for the development of emerging technologies, recently announced an investment of $2 billion (£1.52 billion) to build the next-gen AI. But the bridges that the Defense Department has tried to build with Silicon Valley have come under pressure due to the employee protests from companies such as Google and Microsoft.
Recent government policies are seen as putting a dampener on the growth of the AI industry. Tightening of the immigration rules is starving Silicon Valley of much needed talent.
Statements from a one-page fact sheet released by the White House and the speech by Michael Kratsios, Deputy Assistant to the President for technology policy, that set the tone for the national strategy:
America has been the global leader in AI and the Trump administration will ensure “our great nation” remains in that position.
President Trump has taken executive action to give US workers the skills to succeed in the 21st-century economy.
China
China announced its ambition to lead the world in AI theories, technologies, and applications in its July 2017 plan, A Next Generation Artificial Intelligence Development Plan. The plan is the most comprehensive of all national AI strategies, with initiatives and goals for R&D, industrialization, talent development, education and skills acquisition, standard setting and regulations, ethical norms, and security. It is best understood as a three step plan: first, make China’s AI industry “in-line” with competitors by 2020; second, reach “world-leading” in some AI fields by 2025; and third, become the “primary” center for AI innovation by 2030. By 2030, the government aims to cultivate an AI industry worth 1 trillion RMB, with related industries worth 10 trillion RMB. The plan also lays out the government’s intention to recruit the world’s best AI talent, strengthen the training of the domestic AI labour force, and lead the world in laws, regulations, and ethical norms that promote the development of AI. The latter includes the intent to actively participate in and lead the global governance of AI.
Since the release of the Next Generation Plan, the government has published the Three-Year Action Plan to Promote the Development of New-Generation Artificial Intelligence Industry. This plan builds on the first step of the Next Generation plan to bring China’s AI industry in-line with competitors by 2020. Specifically, it advances four major tasks: (1) focus on developing intelligent and networked products such as vehicles, service robots, and identification systems, (2) emphasize the development AI’s support system, including intelligent sensors and neural network chips, (3) encourage the development of intelligent manufacturing, and (4) improve the environment for the development of AI by investing in industry training resources, standard testing, and cybersecurity. In addition, the government has also partnered with national tech companies to develop research and industrial leadership in specific fields of AI and will build a $2.1 billion technology park for AI research in Beijing.
Russia
President Putin’s assertion that “whoever becomes the leader in this sphere will become the ruler of the world” is frequently used by observers as evidence of a global AI arms race. But Putin’s statement is often quoted without context and, as a result, vastly overstates Russia’s AI capabilities. Speaking to students during a national “open lesson” on the first day of the school year in September 2017, Putin was asked a question about AI. He responded with the above quote, but also stated that “it would not be very desirable that this monopoly be concentrated in someone’s specific hands. That’s why, if we become leaders in this area, we will share this know-how with the entire world.” Putting aside whether or not Russia would actually share its AI technology with the world, this part of the quote is a crucial omission of Russia’s AI capabilities. “If we become leaders in this area” confirms that Russia is far from being a leader in the global AI race and is instead hustling to catch up. As Samuel Bendett reports for Defense One, “Russia’s annual domestic investment in AI is probably around 700 million rubles ($12.5 million) — a paltry sum next to the billions being spent by American and Chinese companies.”
In March 2018, Russia’s Ministry of Defence, the Ministry of Education and Science, and the Russian Academy of Sciences hosted a conference titled, “Artificial Intelligence: Problems and Solutions — 2018.” As a result of the conference, the Ministry of Defence released a list of 10 policies that the conference recommended. While the list is not an official strategy for the Russian government, it does lay the foundation for a national AI strategy. Key recommendations include creating a state system for AI education and talent retainment, establishing a national center for AI, and hosting war games to study the impact of AI on military operations.
Two Possible Futures
Data is the commodity of this century and the way we use it will shape how we live our lives in the future. Politicians are slowly coming to understand the importance of mastering the use of data to address the challenges society faces. At the same time, tech companies are developing tools and services to understand the needs and interests of citizens in a more precise way than governments will ever be able to, with many of these products already being implemented in cooperation with governments around the world.
The increasing dependence on algorithms and machines in decision-making raises questions of legitimacy. Automating decisions based on big amounts of data makes it difficult to hold governments to account as algorithms get more sophisticated and people who designed the rationale behind them are less capable of understanding them. Assuming that automated data will be an inherent part of governments and their interactions with the society, two possible futures can be imagined.
The increasing dependence on algorithms and machines in decision-making raises questions of legitimacy. On the positive spectrum, data can help optimise resources, increase transparency, foster learning and optimise individual choices. On the negative side, data can be used for social control, to reinforce biases, misinform, or make government actions less accountable.
Data usage has the potential to dramatically change life as we know it. The way we overcome the challenges and exploit the opportunities it brings will guide the future we will build. If basic standards of privacy and accountability are in place, data can help improve the relationship between governments and their citizens. However, governments alone cannot address these challenges only by using regulation: tech companies need to take action to build a healthier online environment as well.
How to Move Towards the Good Version of a Data-Driven Future
In order to explore the positive outcomes of data usage, governments, private companies, and civil society need to think outside of the box, not only offering regulation as a solution, but a multi-stakeholder approach to this question.
With significant job cuts expected in the wake of automation, governments need to think about offering a mix of training and social security policies to facilitate the transition of workers in the labour market in the short run. In the long term, educational systems and redistributive policies need to align with the effects of these trends, if we want to avoid profits from technological development going only to those at the top.
But government does have an important role to play. Data protection laws should dictate the rules of what can and what cannot be done. Without comprehensive protection of citizens’ personal data and ways to verify and make those who develop machine learning applications accountable, it will be difficult to ensure that we explore the full potential of innovation without avoiding its risks.
If a democratic government neglects its duty to regulate data usage, it may find its power short-lived. The idea of a machine automating decisions that should be in the hands of public authorities challenges the social contract that exists between voters and elected officials. This issue should be on the public agenda if politicians want to avoid criticism about the lack of transparency and accountability that automation may bring. Governments should foster open-data and open-government initiatives in order to allow civil society to hold authorities accountable for their actions.
Both futures are possible, and we will likely live a world in which both of them coexist. The way we guide the use of technology in government and in civil society will determine whether we can take advantage of its benefits or live in fear of its consequences. We should not blame technology, but rather make it work for all of us.
What is the HiPPO Effect?
Avinash Kaushik was the first to coin the term HiPPO in his book Web Analytics: An Hour a Day. When a HiPPO is in the room and a difficult decision needs to be made but there’s not data or data analysis to determine the right course of action one way or another, the group will often defer to the judgement of the HiPPO. HiPPOs usually have the most experience and power in the room. Once their opinion is out, voices of dissent are usually shut out and in some cases, based on the culture, others fear speaking out against the HiPPO’s direction even if they disagree with it.
When Ron Johnson, former head of retail at Apple who was responsible for the highly profitable Apple Stores, took over as CEO at J.C. Penney, he suffered from the HiPPO Effect. Without reviewing the existing data or investing in new data about the very different retail store he was now leading, he went full throttle ahead on his strategy for the department store chain. When his strategy was launched and he checked in to see if it was working, few had the courage to give him the unvarnished truth and be labeled as a resistor. Needless to say, his strategy wasn’t succeeding with J.C. Penney’s customers.
https://finance.yahoo.com/news/jc-penneys-controversial-former-ceo-is-unsure-if-the-retailer-will-be-around-in-5-years-145259863.html
The Harvard Business Review found that while 80 percent of survey respondents rely on data in their roles and 73 percent rely on data to make decisions, 84 percent still said managerial judgment is a factor when making key decisions.
If you are the HiPPO, follow the example of Alfred Sloan, long-term president, chairman and CEO of General Motors who “had a strong belief about making decisions; they shouldn’t be made until someone had expressed why the ‘preferred’ option might not be the right one.” Invite disagreement; make yours a culture that you seek multiple opinions and even ask someone to play devil’s advocate prior to an important decision being made.
A college degree at the start of a working career does not answer the need for the continuous acquisition of new skills, especially as career spans are lengthening. Vocational training is good at giving people job-specific skills, but those, too, will need to be updated over and over again during a career lasting decades. – The Economist
Fortunately it doesn’t take much time or money to boost your skills to make you more competitive. You just need to have a strategy for ensuring that your knowledge and skills are always up-to-date. Even if you aren’t in a technical job, technical skills like software and social media help everyone. Creative skills like graphic design and photography are also useful in a variety of jobs. Skills like project management, team leadership, and conflict resolution are critical to anyone’s success. In short, knowledge work is an area that will continue to grow; career options will become more varied and require ongoing education to remaining current.
2nd last slide. Final slide will be the same as the 1st slide.
