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The State of Digital Investments in MENA 2013-2018 Report

Synopsis: This research report investigates the technology investment landscape in the Middle East and North Africa (MENA) region by analyzing investments made by MENA-based investors into MENA-based startups. The analysis is based on data collected directly from 59 investors and accelerators across the MENA region, specifically in the United Arab Emirates, Saudi Arabia, Lebanon, Kuwait, Jordan, Oman, Egypt, Bahrain, Morocco, Tunisia, Palestine, and Yemen. The report analyzes 1,423 regional investments.

Please go to the below mentioned web link for downloading the full report:


Finance – Fund Management / Fintech Trends To Watch In 2019
« on: October 05, 2019, 05:36:11 PM »
Web link of Fintech Trends To Watch In 2019:


Research shows that human beings have the talent to deceive one another and be dishonest; a talent that they often use. This is mainly since it allows humans to manipulate others without using physical force. Harvard University’s Sissela Bok says that “It’s much easier to lie in order to get somebody’s money or wealth than to hit them over the head or rob a bank.”

It is thus not surprising that despite the corporate governance lapses of the early 2000s and the measures taken thereafter (Sarbanes Oxley, various codes of corporate governance, numerous board directors’ training programs, etc.) we are still witness (in 2019) to a great many governance failures on a daily-basis. This only goes to show that unless these ethical and governance standards are embraced by individuals and companies in spirit and not just in letter, not much will change in the way we govern our businesses – or in the way we use available tools, including technology, to maximize profits. Apparently, us humans still require being told what the ethical boundaries are, and we still need to be supervised to ensure that we do not fall out of step. This is where regulations and regulatory oversight come into play.

In today’s technology-driven world with “innovation” happening all around us, we can often see that regulations are always trying to catch up with the new business models. Such new ideas and business models are being introduced at a very high frequency, and most of the time the regulatory support required to protect systemic failures is not there. However, many of these new business models are addressing a need and demand in the market and thus relevant in terms of their use case. As such, we see regulators struggling to keep pace with the innovations keeping in view their role as protectors of both the system and the consumers of products and services.

One of the early adopters of technology has been the finance and banking sector. We know that the major advantage of technology is its ability to process information at very high speeds enabling quicker and better business decision making. Within the banking sector ML and AI (Artificial – or more aptly Augmented Intelligence) are being used for this purpose, mainly in the areas of Risk Management, Compliance, Credit, KYC and Cyber Security. To do this, technology needs to collect and process huge amounts of data, most of which is generated by the actions of human beings through digitalized processes. This enables designing algorithms to generate valuable insights from the collected data. It is data (both quality and quantity) that fuels the ability of ML/AI to derive insights for improved and swifter decisioning.  The manner, in which AI is now deployed has undergone a lot of changes over the years. Today, it is applied and used in anything from chat-bots, robots and autonomous cars. Thus, the quest for more and more data, and seeking more and more business opportunities for using and monetizing that data, has become a primary objective of most institutions. Herein, lies the problem.

Research also shows that creative people are more likely to exhibit unethical behavior when faced with ethical dilemmas. Thus, while innovation continues to take place in the absence of adequate regulatory frameworks, we see two things happening – either the pace of innovation is slowed or even stopped; or innovation continues in parallel with the designing of regulatory regimes. It is here, and during this lag period, that dishonesty and unethical practices can and do take place. This then begs the question whether innovation should wait till the regulatory regime is perfected – or should the innovators cooperate and work with the regulators and help them design an “innovation-friendly” regulatory framework. Given market dynamics, I would vote for the latter. However, this can only happen if during the period when the regulatory framework is weak and evolving, the innovators (and users of innovative technologies) are acting responsibly and ensuring that technology is not being misused. Unfortunately, thus far we have seen that technology has been misused on several occasions (I am sure I do not need to delve into Cambridge Analytics, Facebook, Google, and the several incidents involving banks, credit bureaus and others over the past many years; I have also written about these in other publications). Unfortunately, what such irresponsible behavior could lead to – and it seems is already leading to - is “over-regulation”, which in turn would stifle innovation, and hence the ability of both the innovators and its users to scale by leveraging technology. Already, we are seeing regulators bringing in the innovators for hours of questioning to try and understand why (and how) they did what they did in terms of data misuse, invasion of privacy, developing biased algorithms resulting in biased decisions, lax oversight and understanding of cyber security issues, (it’s a long list), etc. By such questioning the regulators are trying to determine what type of regulatory frameworks and oversight need to be developed because of irresponsible behavior.

In today’s world of digital technology, while there is ample opportunity to improve the way products and services are delivered and make processes more efficient, there is also certainly a lot of room for dishonest practices, using the same technology. For this reason, the onus is on all stakeholders - the innovators, the users of innovations, the consumers and the regulators - to ensure that technology can be leveraged strategically and sustainably. This can only happen if we realize that with the great power that technology gives to all of us, the burden of responsible behavior is even greater and heavier. And unless we live up to the responsibilities that we need to display, the use of technology might not be sustainable.


TEACHERS UNDER THE MICROSCOPE (an article published in The Daily Star)

For the purposes of this article, we conducted a survey and got responses from 195 students from public and private universities (57 percent and 43 percent respectively) in different semesters (39.2 percent: 1st to 4th semesters; 44.4 percent: 4th to 8th semesters; 5.8 percent: 9th to 12th semesters; 4.8 percent: over 12 semesters) with 47 percent having a CGPA above 3.5 and 53 percent having a CGPA below 3.5.


When semesters are about to end, students in many universities are asked to complete faculty evaluations. In some universities, these are mandatory. In others, they are non-existent. Regardless, many students go to social media to vent about their professors and lecturers. Their complaints are many, and such posts often have numerous people sharing their own stories about faculties who in their words are “unfair”, “biased” or “unfriendly”.

In our survey, when asked whether students believed that working hard would always get them an A, 114 of the 193 who answered chose “No, the teacher can sometimes be biased or unfair” with 78 choosing “Yes” and 56 choosing “No, not everyone is capable”. Again in another question, 45.8 percent (88 out of 192 students) said they got bad grades because “The teacher can sometimes be biased or unfair”.

It is common to see students getting upset over the grades they get. Many seem to believe that if you work hard, it should automatically translate to a good grade. However, students often completely miss the point of assignments or provide irrelevant answers to questions, even on tests that they studied well for. Rote memorisation doesn’t always pay off, and there are test-taking skills one must master if one expects to do well. Students don’t always know what a teacher expects from them, and this sometimes creates confusion and anger as some feel that they deserve better grades.

Do students themselves consider the complaints of other students regarding the validity of the marks they get from their teachers? Our results were inconclusive with half saying “yes” and half saying “no”.

When asked what a good teacher is to them, a majority of the 193 students (167 or 86.5 percent) chose “Creates a positive learning experience”, but 32.6 percent (or 63 students) chose “Is easy-going and not strict when grading”; a small 11.9 percent chose “Doesn’t expect too much from students” and very few chose “Gave you good grades” and “Curves/inflates grades”.

Another one of the expectations that students seem to have is that teachers will inflate grades. In our survey, 47.6 percent of the students responded that they believe all teachers should inflate grades. Whether these expectations are justified is a matter of debate, but what is clear is that students are often seen in a negative light.


Ask anyone who has been in a group project, and you’ll see that university students themselves don’t have the best reputation even amongst themselves.

A 2018 article on Star Weekend discusses how Nilkhet’s flourishing business shows just how many students look for readymade academic papers. It becomes hard to root for students when one sees the extent of academic dishonesty. Professors become massively frustrated, and negative formal evaluations and comments can demoralise them, even if it doesn’t directly affect their situation at work.


Current university students are products of an education system that is far from ideal. Many have had to sit for not just two, but three major public exams while still in school, causing enormous stress at a young age. Exacerbating this problem is the low level of English proficiency among students. With English being the medium of instruction in all—if not most—universities, students end up having to learn in a language they are not fully comfortable using.

More importantly, this generation of university students not only have a massive workload, they have also started working earlier than those before them. As a result, many have to routinely balance work and studies. The pressure is even greater for those who’ve come from outside Dhaka and now have to adjust to a new city, often away from their friends and families for the first time.

To their credit, students do seem to have some level of awareness. Of the students who answered the question of whether they felt that students were entitled, 43.5 percent said “Yes”, 45.5 percent said “Only some are” and the rest said “No”. To the question of why some students thought they got bad grades in a course, a majority (114) chose “Didn’t study enough for it”. Eighty-eight students (45.8 percent) chose “The faculty can sometimes be biased or unfair”, 20 students (10.4 percent) chose “The faculty didn’t curve/inflate my grades” and 59 students (30.7 percent) chose “I struggled but eventually got a desirable grade”.

However, what must be acknowledged is that students don’t always know what’s best for them. A professor whose class they dread now might actually be the class that benefits them the most in the future.


Criticism of student evaluation of teaching isn’t new. How can students decide what quality education is or judge a teacher’s competence when experts cannot say for certain what a good education is? In an article by Henry A. Hornstein, the various problems with students evaluating teachers are discussed. He writes, “Students can reliably speak about their experience in a course. However, they cannot evaluate outside their experience, i.e. how can they access course pedagogy? By what valid criteria are students able to determine how “knowledgeable” an instructor is about his/her subject area?”

In addition, there is an assumption that the students evaluating will be doing it objectively. Tasnova Humaira, Lecturer at BRAC University, says, “Students may sometimes evaluate negatively because of one bad experience with the teacher, or might evaluate without giving any real thought to the process.”

She adds, “Student feedback is essential in creating an effective classroom environment where students can genuinely reflect on previous knowledge, learn new information and question different ideas without any anxiety.”

Similarly, in a 2010 article in The Daily Star, Abul Bayes, a professor at Jahangirnagar University, defends student evaluations of teachers and writes, “Only an accountable person is a respectable person.”


A major problem seems to be the lack of transparency and communication between professors and students. When asked what practices teachers engage in that negatively affects students, most chose “Being impatient and unfriendly”. However, 83 students chose “Not showing exam scripts and assignments”, 121 chose “Not explaining to a student why marks were cut” and 38 chose “Losing exam scripts, assignments, and homework”. In turn, 58.3 percent of students said they did not feel that teachers are overworked.

It becomes obvious when looking at this information—both parties could clearly benefit from more discussion. This is further supported by the answers we got to the question of what a good teacher is to a student and the second most chosen option with 78.2 percent selecting “Openly communicates with students about grades, topics discussed in class, etc”.

Students have a right to question their professors and lecturers when they get a grade they feel is wrong. They have a right to know what their mistakes are. And so it is unfair to immediately label all students with complaints as immature and unwilling to take responsibility for their actions. While it is true that many want as easy a workload as possible, many genuinely have difficulty understanding some things.Overall, listening to students might make the journey smoother, both for the university and the students. Student evaluations of teachers might be one of the important ways in which institutions listen to what students have to say.

Aliza is Matilda resurrected. Reach her at


Nurturing the changemakers of tomorrow
by Md. Sabur Khan, Chairman, Board of Trustees, Daffodil International University

Entrepreneurs are harbingers of hope. To promote and nourish entrepreneurship, many countries have given substantial attention to entrepreneurship education and strengthening related institutions. Management gurus view entrepreneurial activities as a critical contributor in fostering economic growth and development.

We have observed that both entrepreneurial initiatives and education have expanded significantly in the US and Israel. You will find that the maximum numbers of unicorns are based in the US and China, such as Ant Financial, Airbnb, SpaceX, OLA Cabs, Rubrik. A unicorn is a privately held startup company valued at over USD 1 billion. Among former unicorns, Uber, Facebook, Xiaomi, Alibaba are the more notable ones. Some perfect examples of entrepreneurial legacies are developed in Silicon Valley in Northern California, Austin TX, San Francisco, CA. To boost entrepreneurial initiatives, the US has also developed a unique culture of Angel Investment Ecosystem. All giant startups and entrepreneurial initiatives have been developed by nurturing the entrepreneurial mindset of people. Qatar is also doing good in the domain of innovation and research; for example, Qatar Foundation is working on education, research, and community development.

In our education system, we do not assess or evaluate a person’s natural talents, innovation or entrepreneurial mindset. An innovator or entrepreneur does not only mean being a successful businessperson; people with an entrepreneurial mindset can contribute or engage themselves in different sectors or segments. Those entrepreneurial minded people may be in government, law enforcement agencies or in the corporate sector. These individuals possess unique traits like creativity, innovativeness, ability to take risks. A nation can only progress by nurturing these people.

To maintain sustainable and equitable development, the tertiary-level education system needs to be transformed, focusing heavily on encouraging and cultivating entrepreneurial minded students. Practical or hands-on experience is needed in our education system. At the tertiary level, our students should be involved in practical experiences. Besides, the country’s education needs to adopt innovation, instead of following the archaic method of teaching-learning. The old system should be replaced by Outcome Based Education (OBE). Effective pedagogy and innovative teaching methods can be applied with entrepreneurial minded academics.

We must take into account one thing, that our education system should also focus on the theme of Sustainable Development Goal (SDG) 4, which aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all”. We also need to think of our future workforce where emerging technologies like Artificial Intelligence, Quantum Computing, Internet of Things (IoTs), Robotics will play a pivotal role in production and manufacturing. According to the McKinsey Global Institute, robots could replace 800 million jobs by 2030, while the World Economic Forum suggests that a “skills revolution” could open up a raft of new opportunities. So, our tertiary education should concentrate on innovation in every area. “If we do not change the way we teach, 30 years from now, we’re going to be in trouble,” said Jack Ma, founder of Alibaba Group, China’s e-commerce giant. The knowledge-based approach of “200 years ago” would “fail our kids”, who would never be able to compete with machines. Children should be taught “soft skills” like independent thinking, values and teamwork, he said.

I believe it is high time we focused on ensuring sustainable education model in the country, where innovation will be an integral part of that process. There are some real-life challenges in the country to establish a good entrepreneurial ecosystem. In tackling the challenges, students should be familiarised with alternative funds like venture capital, angel investment, etc.

At Daffodil International University, we have already planned to introduce courses on robotics in each department. A good number of them have already started their own ventures, which has been facilitated by this holistic initiative. We believe entrepreneurial education creates high job satisfaction. Higher levels of entrepreneurial education achievement lead to higher earnings and reduce the level of unemployment. Of late, many universities around the world are in the process of strengthening their entrepreneurship education programmes in order to create more young entrepreneurs in the future.

We are pretty hopeful as our government formulates various pro-entrepreneurial policies. The government is already set to form a specialised firm (to be called Startup Bangladesh Company Limited), to fund and nurture startups and ICT entrepreneurs under the Innovation Design and Entrepreneur Academy of the ICT division with the view to encouraging innovative ventures in Bangladesh, which is a unique and holistic initiative. It is worth mentioning here that Dhaka Chamber of Commerce and Industry, in association with Bangladesh Bank, has organised Creating 2000 Entrepreneurs (E2K) in the country. We hope the central bank will come up with more such initiatives to contribute in creating entrepreneurs in the country. The initiative has given the direction to nurture the entrepreneurship process, which was acknowledged and accepted by the government.

Imran Khan, former Chief Strategy Officer of Snap Inc., at a national debate programme remarked: “My talent will not be nourished here; that’s why I have decided to go to the US.” Though it was meant to be a light-hearted comment, it sums up the situation and highlights how we need to stop the brain drain by providing entrepreneurial facilities to the young generation.

Bangladesh has enormous opportunities to grow more. According to a World Bank report, Bangladesh is among the five fastest-growing economies of the world, with a 7.3 percent GDP growth projection in the FY2019. The report also added that Bangladesh’s growth outlook remains strong and stable. Sound macroeconomic policies—such as keeping the budget deficit below 5 percent of GDP—and resilient domestic demand have led to growth in manufacturing and construction industries on the supply side. On the demand side, growth is led by private consumption and exports. Aligning with this trajectory, quality in tertiary education plays a vital role, as the world is now moving towards the fifth industrial revolution. For sustainable growth, we need to build a skilled pool of human resources.

I strongly believe our young population can adjust well, with their inherent power to transform, and can retain the existing progress of the country where entrepreneurial mindset and innovation will work as a catalyst. The new generation of our country needs to be educated and trained up in such a way that they will believe in their own minds that they can become successful entrepreneurs, who will not have to search for jobs, rather will provide jobs to others as Bangladesh works to transform into a “developed country”.


৫০০ কোটি টাকা মূলধনের সরকারি স্টার্টআপ কোম্পানির অনুমোদন

টেক শহর কনটেন্ট কাউন্সিলর : দেশের উদ্যোক্তারা এই কোম্পানি হতে কোনো জামানত ছাড়াই সর্বোচ্চ ৫ কোটি টাকা পর্যন্ত পেতে পারেন। মূলত স্টার্টআপে বিনিয়োগ ও উদ্যোক্তা সংস্কৃতি গড়তে তথ্যপ্রযুক্তি বিভাগের একোম্পানি গঠনের প্রস্তাবে অনুমোদন দিয়েছে সরকার । কোম্পানিটি প্রতিষ্ঠিত হবার পরে স্টার্টআপদেরকে মূল্যায়নের প্রেক্ষিতে সীড স্টেজে সর্বোচ্চ ১ কোটি এবং গ্রোথ গাইডেড  স্টার্টআপ রাঊন্ডে  সর্বোচ্চ ৫ কোটি টাকা বিনিয়োগ করতে পারবে।‘স্টার্টআপ বাংলাদেশ কোম্পানি লিমিটেড’ গঠনের ওই প্রস্তাব সোমবার মন্ত্রিসভার বৈঠকে অনুমোদন দেয়া হয়।প্রধানমন্ত্রীর কার্যালয়ে অনুষ্ঠিত বৈঠকটিতে সভাপতিত্ব করেছেন প্রধানমন্ত্রী শেখ হাসিনা।বৈঠক শেষে সচিবালয়ে মন্ত্রিপরিষদ সচিব মোহাম্মদ শফিউল আলম সাংবাদিকদের জানান, উদ্যোক্তারা আইডিয়া দিয়েই এই কোম্পানি হতে টাকা পাবেন। ব্যাংকে লোক পেতে যে মর্টগেজসহ কতকিছু লাগে এখানে তার কিছুই লাগবে না।এখানে ঋণের পরিমাণ ও সুদের হার কত হবে তা কোম্পানি কাজ শুরু করলে ঠিক করা হবে বলে জানান তিনি।৫০০ কোটি টাকা কোম্পানিটির অনুমোদিত মূলধন হবে। পরিশোধিত মূলধন হিসেবে ২০০ কোটি টাকা নিয়ে যাত্রা শুরু হবে কোম্পানির।  নিয়ে যাত্রা শুরু করবে। ১০ টাকা হবে একেকটি শেয়ারের অভিহিত মূল্য।কোম্পানির চেয়ারম্যান হবে তথ্যপ্রযুক্তি সচিব। পরিচালকের সংখ্যা হবে ৭ জন। বিভিন্ন মন্ত্রণালয়ের সচিব ও অতিরিক্ত সচিব পদ মর্যাদার কর্মকর্তারা পর্ষদে থাকবেন। এতে ৩৬ জন জনবল থাকার কথা রয়েছে ।এদিকে চলতি বাজেটে স্টার্টআপ খাতে অর্থমন্ত্রী ১০০ কোটি টাকা বরাদ্দ রেখেছেন।

২০১৬ সাল থেকে স্টার্টআপ বাংলাদেশ প্রকল্পের আওতায় এ নিয়ে কাজ করছে আইসিটি বিভাগ। এরপর থেকে এ সংক্রান্ত একটি কোম্পানির গঠনের কার্যক্রম শুরু হয়। নানা ধাপ পেরিয়ে অবশেষে এ বিষয়ক প্রস্তাব সম্প্রতি মন্ত্রিসভায় উপস্থাপনের প্রক্রিয়া শেষ করা হয়।তথ্যপ্রযুক্তি প্রতিমন্ত্রী জুনাইদ আহমেদ পলক জানিয়েছিলেন, এই কোম্পানির মাধ্যমে ২০২১ সালের মধ্যে দেশের এক হাজার স্টার্টআপের পাশে দাঁড়াবেন তারা।কোম্পানির কাজ হবে মূলত বিকাশমান স্টার্টআপের পাশে দাঁড়ানো। এ ক্ষেত্রে সম্ভাবনাময় স্টার্টআপগুলোতে এই কোম্পানি থেকে বিনিয়োগ করার পাশাপাশি সেগুলোর পরিচালনার অংশীদারও হবে।‘সরকারের এক হাজার কোম্পানিতে বিনিয়োগের লক্ষ্য থেকে যদি একটি বিশ্বমানের কোম্পানি বেরিয়ে আসে তাহলে তা পুরাে দেশের চেহারা বদলে দেওয়ার জন্য যথেষ্ট হবে,’ বলেছিলেন পলক।প্রতিমন্ত্রী বলেছিলেন, সরকার চায় না শিক্ষিত তরুণ শুধু চাকরি খুঁজবে, বরং তারা নতুন চাকরির ব্যবস্থা করবে। সে জন্য দেশে স্টার্টআপ সংস্কৃতি গড়ে তোলা দরকার।


3 priorities for CEOs in 2019

I had a really strong sense of déjà vu when, a little over a year ago, I was elected as KPMG’s new Global Chairman. I felt the same sense of excitement and trepidation I had when, eight years before, I’d taken over as CEO for KPMG Canada. Transformation driven by technology, geopolitical risk and uncertainty, new regulation and competitors all dominated my thinking.

Pretty much every CEO I speak to has a very similar story. Nothing truly prepares you for this kind of role. Being a subject matter or technical expert, leading a country or a global division develops many of the necessary leadership skills and capabilities, but nothing really prepares you for the breadth and pace of issues you’ll face as a CEO.

Most of the CEOs I talk to feel that the Fourth Industrial Revolution – characterized by a fusion of physical, digital and bio technologies – means the job is only going to get tougher.

That anecdotal feedback that I heard as I’ve travelled the world is backed up by our research. We’ve spoken to over 1,300 CEOs leading many of the world’s largest global businesses and found that the best are finding opportunities in this disruption, changing their products and services faster than ever before, and in some cases their entire business model. And those market leading CEOs also recognize the need to develop, and even reshape, their own skills to take on the new challenges they face.

So what are we hearing and, perhaps more importantly, what do CEOs need to focus on in 2019 and beyond to make sure they can successfully lead their businesses through this tumultuous period?

1. Make digital a personal crusade

CEOs need to embrace the digital agenda like never before. Digital is now at the core of virtually every business. I was speaking to the CEO of a large cement manufacturer in South America who brought this home to me when he said he now runs a digital business, where the key decisions he takes are based on data and analytics and computer modelling to forecast future demand, energy pricing and the most efficient forms of delivery.

Setting a digital strategy and leading a digital transformation can’t be delegated. The costs, and stakes, for every business are simply too high.

Yet most CEOs did not get to their leadership role because of their digital background or expertise. Over 70% of the CEOs we spoke to believe they need to lead a radical digitally-led transformation of their business model, and that requires CEOs focusing on their own digital capabilities, learning new skills and being prepared to acknowledge where their knowledge stops, and finding trusted advisers to help shape their decisions.

Understanding cloud, the impact of AI on the workforce, and the fundamentals of cybersecurity are increasingly becoming table stakes for CEOs.

CEOs also recognize that they have a very personal responsibility to protect their customers’ and their employees’ data. Hardly a week goes by without another high-profile media story about a breach of data security. Almost 60% of the CEOs we talked to told us they not only understand this new data paradigm, but they already see protecting customer data as their personal responsibility, and the potential personal consequences for their role if there is a major customer data loss on their watch.

So every CEO has to prioritize and invest the time needed to develop their own digital skills and stay on top of the critical digital issues that they will be held accountable for.

2. Navigate through geopolitical headwinds

Increased geopolitical risk – the threat of political disruption to international trade and investment – has risen to the top of most of the Board agendas for the companies I speak with. And the CEOs we spoke with rated a return to territorialism as the number one threat facing their business.

CEOs understand that they need to hone their global political knowledge and skills and engage with the politicians and civil society leaders, while remaining politically neutral.

CEOs are also acutely aware of the need to build and sustain trust. They tell us that strengthening trust with their important stakeholders is one of the things they know they need to do to reduce the threat posed to their businesses by losing that trust. This is one of the things I see first-hand at KPMG, and we are embarking on a comprehensive programme of initiatives to ensure we can be the most trusted and trustworthy adviser to our clients.

How CEOs see their role in protecting customer data, by country

3. Finding the right balance between data and intuition

We found a surprising digital paradox. CEOs, and the companies they lead, are investing and spending more money on data driven insights than ever before. Yet nearly 70% of the CEOs we spoke to admitted they have relied on their own intuition over data-driven insights to make strategic decisions in the past three years.

More than half of the CEOs we spoke to are less confident in the accuracy of predictive analytics compared to historic data, and have the highest trust for social media sources over all others.

CEOs need to find a better balance between data and intuition, and that inevitably involves spending more time getting deeper into the way that data driven insight for their business is being developed, and how it is used to shape strategy and operational decisions.


Concerns of an Artificial Intelligence Pioneer
n January, the British-American computer scientist Stuart Russell drafted and became the first signatory of an open letter calling for researchers to look beyond the goal of merely making artificial intelligence more powerful. “We recommend expanded research aimed at ensuring that increasingly capable AI systems are robust and beneficial,” the letter states. “Our AI systems must do what we want them to do.” Thousands of people have since signed the letter, including leading artificial intelligence researchers at Google, Facebook, Microsoft and other industry hubs along with top computer scientists, physicists and philosophers around the world. By the end of March, about 300 research groups had applied to pursue new research into “keeping artificial intelligence beneficial” with funds contributed by the letter’s 37th signatory, the inventor-entrepreneur Elon Musk.

Russell, 53, a professor of computer science and founder of the Center for Intelligent Systems at the University of California, Berkeley, has long been contemplating the power and perils of thinking machines. He is the author of more than 200 papers as well as the field’s standard textbook, Artificial Intelligence: A Modern Approach (with Peter Norvig, head of research at Google). But increasingly rapid advances in artificial intelligence have given Russell’s longstanding concerns heightened urgency.

Recently, he says, artificial intelligence has made major strides, partly on the strength of neuro-inspired learning algorithms. These are used in Facebook’s face-recognition software, smartphone personal assistants and Google’s self-driving cars. In a bombshell result reported recently in Nature, a simulated network of artificial neurons learned to play Atari video games better than humans in a matter of hours given only data representing the screen and the goal of increasing the score at the top — but no preprogrammed knowledge of aliens, bullets, left, right, up or down. “If your newborn baby did that you would think it was possessed,” Russell said.

Quanta Magazine caught up with Russell over breakfast at the American Physical Society’s 2015 March Meeting in San Antonio, Texas, where he touched down for less than 24 hours to give a standing-room-only lecture on the future of artificial intelligence. In this edited and condensed version of the interview, Russell discusses the nature of intelligence itself and the immense challenges of safely approximating it in machines.

QUANTA MAGAZINE: You think the goal of your field should be developing artificial intelligence that is “provably aligned” with human values. What does that mean?
STUART RUSSELL: It’s a deliberately provocative statement, because it’s putting together two things — “provably” and “human values” — that seem incompatible. It might be that human values will forever remain somewhat mysterious. But to the extent that our values are revealed in our behavior, you would hope to be able to prove that the machine will be able to “get” most of it. There might be some bits and pieces left in the corners that the machine doesn’t understand or that we disagree on among ourselves. But as long as the machine has got the basics right, you should be able to show that it cannot be very harmful.

How do you go about doing that?
That’s the question I’m working on right now: Where does a machine get hold of some approximation of the values that humans would like it to have? I think one answer is a technique called “inverse reinforcement learning.” Ordinary reinforcement learning is a process where you are given rewards and punishments as you behave, and your goal is to figure out the behavior that will get you the most rewards. That’s what the [Atari-playing] DQN system is doing; it is given the score of the game, and its goal is to make that score bigger. Inverse reinforcement learning is the other way around. You see the behavior, and you’re trying to figure out what score that behavior is trying to maximize. For example, your domestic robot sees you crawl out of bed in the morning and grind up some brown round things in a very noisy machine and do some complicated thing with steam and hot water and milk and so on, and then you seem to be happy. It should learn that part of the human value function in the morning is having some coffee.

There’s an enormous amount of information out there in books, movies and on the web about human actions and attitudes to the actions. So that’s an incredible resource for machines to learn what human values are — who wins medals, who goes to jail, and why.

Video: DQN, an artificial neural network developed by researchers at Google DeepMind, teaches itself to play Atari games such as Breakout. It quickly develops sophisticated strategies.
How did you get into artificial intelligence?
When I was in school, AI wasn’t thought of as an academic discipline, by and large. But I was in boarding school in London, at St. Paul’s, and I had the opportunity to avoid compulsory rugby by doing a computer science A-level [course] at a nearby college. One of my projects for A-level was a program that taught itself to play naughts and crosses, or tic-tac-toe. I became very unpopular because I used up the college’s computer for hours on end. The next year I wrote a chess program and got permission from one of the professors at Imperial College to use their giant mainframe computer. It was fascinating to try to figure out how to get it to play chess. I learned some of the stuff I would later be teaching in my book.

But still, this was just a hobby; at the time my academic interest was physics. I did physics at Oxford. And then when I was applying to grad school I applied to do theoretical physics at Oxford and Cambridge, and I applied to do computer science at MIT, Carnegie Mellon and Stanford, not realizing that I’d missed all the deadlines for applications to the U.S. Fortunately Stanford waived the deadline, so I went to Stanford.

And you’ve been on the West Coast ever since?

You’ve spent much of your career trying to understand what intelligence is as a prerequisite for understanding how machines might achieve it. What have you learned?
During my thesis research in the ’80s, I started thinking about rational decision-making and the problem that it’s actually impossible. If you were rational you would think: Here’s my current state, here are the actions I could do right now, and after that I can do those actions and then those actions and then those actions; which path is guaranteed to lead to my goal? The definition of rational behavior requires you to optimize over the entire future of the universe. It’s just completely infeasible computationally.

It didn’t make much sense that we should define what we’re trying to do in AI as something that’s impossible, so I tried to figure out: How do we really make decisions?

So, how do we do it?
One trick is to think about a short horizon and then guess what the rest of the future is going to look like. So chess programs, for example — if they were rational they would only play moves that guarantee checkmate, but they don’t do that. Instead they look ahead a dozen moves into the future and make a guess about how useful those states are, and then they choose a move that they hope leads to one of the good states.

Could you prove that your systems can’t ever, no matter how smart they are, overwrite their original goals as set by the humans?

Another thing that’s really essential is to think about the decision problem at multiple levels of abstraction, so “hierarchical decision making.” A person does roughly 20 trillion physical actions in their lifetime. Coming to this conference to give a talk works out to 1.3 billion or something. If you were rational you’d be trying to look ahead 1.3 billion steps — completely, absurdly impossible. So the way humans manage this is by having this very rich store of abstract, high-level actions. You don’t think, “First I can either move my left foot or my right foot, and then after that I can either…” You think, “I’ll go on Expedia and book a flight. When I land, I’ll take a taxi.” And that’s it. I don’t think about it anymore until I actually get off the plane at the airport and look for the sign that says “taxi” — then I get down into more detail. This is how we live our lives, basically. The future is spread out, with a lot of detail very close to us in time, but these big chunks where we’ve made commitments to very abstract actions, like, “get a Ph.D.,” “have children.”

Are computers currently capable of hierarchical decision making?
So that’s one of the missing pieces right now: Where do all these high-level actions come from? We don’t think programs like the DQN network are figuring out abstract representations of actions. There are some games where DQN just doesn’t get it, and the games that are difficult are the ones that require thinking many, many steps ahead in the primitive representations of actions — ones where a person would think, “Oh, what I need to do now is unlock the door,” and unlocking the door involves fetching the key, etcetera. If the machine doesn’t have the representation “unlock the door” then it can’t really ever make progress on that task.

But if that problem is solved — and it’s certainly not impossible — then we would see another big increase in machine capabilities. There are two or three problems like that where if all of those were solved, then it’s not clear to me that there would be any major obstacle between there and human-level AI.

What concerns you about the possibility of human-level AI?
In the first [1994] edition of my book there’s a section called, “What if we do succeed?” Because it seemed to me that people in AI weren’t really thinking about that very much. Probably it was just too far away. But it’s pretty clear that success would be an enormous thing. “The biggest event in human history” might be a good way to describe it. And if that’s true, then we need to put a lot more thought than we are doing into what the precise shape of that event might be.

The basic idea of the intelligence explosion is that once machines reach a certain level of intelligence, they’ll be able to work on AI just like we do and improve their own capabilities — redesign their own hardware and so on — and their intelligence will zoom off the charts. Over the last few years, the community has gradually refined its arguments as to why there might be a problem. The most convincing argument has to do with value alignment: You build a system that’s extremely good at optimizing some utility function, but the utility function isn’t quite right. In [Oxford philosopher] Nick Bostrom’s book [Superintelligence], he has this example of paperclips. You say, “Make some paperclips.” And it turns the entire planet into a vast junkyard of paperclips. You build a super-optimizer; what utility function do you give it? Because it’s going to do it.

What about differences in human values?
That’s an intrinsic problem. You could say machines should err on the side of doing nothing in areas where there’s a conflict of values. That might be difficult. I think we will have to build in these value functions. If you want to have a domestic robot in your house, it has to share a pretty good cross-section of human values; otherwise it’s going to do pretty stupid things, like put the cat in the oven for dinner because there’s no food in the fridge and the kids are hungry. Real life is full of these tradeoffs. If the machine makes these tradeoffs in ways that reveal that it just doesn’t get it — that it’s just missing some chunk of what’s obvious to humans — then you’re not going to want that thing in your house.

I don’t see any real way around the fact that there’s going to be, in some sense, a values industry. And I also think there’s a huge economic incentive to get it right. It only takes one or two things like a domestic robot putting the cat in the oven for dinner for people to lose confidence and not buy them.

Then there’s the question, if we get it right such that some intelligent systems behave themselves, as you make the transition to more and more intelligent systems, does that mean you have to get better and better value functions that clean up all the loose ends, or do they still continue behaving themselves? I don’t know the answer yet.

You’ve argued that we need to be able to mathematically verify the behavior of AI under all possible circumstances. How would that work?

Automating air traffic control systems may require airtight proofs about real-world possibilities.

One of the difficulties people point to is that a system can arbitrarily produce a new version of itself that has different goals. That’s one of the scenarios that science fiction writers always talk about; somehow, the machine spontaneously gets this goal of defeating the human race. So the question is: Could you prove that your systems can’t ever, no matter how smart they are, overwrite their original goals as set by the humans?

It would be relatively easy to prove that the DQN system, as it’s written, could never change its goal of optimizing that score. Now, there is a hack that people talk about called “wire-heading” where you could actually go into the console of the Atari game and physically change the thing that produces the score on the screen. At the moment that’s not feasible for DQN, because its scope of action is entirely within the game itself; it doesn’t have a robot arm. But that’s a serious problem if the machine has a scope of action in the real world. So, could you prove that your system is designed in such a way that it could never change the mechanism by which the score is presented to it, even though it’s within its scope of action? That’s a more difficult proof.

Are there any advances in this direction that you think hold promise?
There’s an area emerging called “cyber-physical systems” about systems that couple computers to the real world. With a cyber-physical system, you’ve got a bunch of bits representing an air traffic control program, and then you’ve got some real airplanes, and what you care about is that no airplanes collide. You’re trying to prove a theorem about the combination of the bits and the physical world. What you would do is write a very conservative mathematical description of the physical world — airplanes can accelerate within such-and-such envelope — and your theorems would still be true in the real world as long as the real world is somewhere inside the envelope of behaviors.

Yet you’ve pointed out that it might not be mathematically possible to formally verify AI systems.
There’s a general problem of “undecidability” in a lot of questions you can ask about computer programs. Alan Turing showed that no computer program can decide whether any other possible program will eventually terminate and output an answer or get stuck in an infinite loop. So if you start out with one program, but it could rewrite itself to be any other program, then you have a problem, because you can’t prove that all possible other programs would satisfy some property. So the question would be: Is it necessary to worry about undecidability for AI systems that rewrite themselves? They will rewrite themselves to a new program based on the existing program plus the experience they have in the world. What’s the possible scope of effect of interaction with the real world on how the next program gets designed? That’s where we don’t have much knowledge as yet.

This article was reprinted on


গুগল স্টেডিয়া: শুরু হতে যাচ্ছে ক্লাউড গেমিংয়ের যুগ

এমন একটি সময়ের কথা ভাবুন, যখন আপনার প্রিয় ওপেন ওয়ার্ল্ড গেমগুলো খেলার জন্য আপনার নিজের কম্পিউটারের ক্ষমতা নিয়ে চিন্তা করতে হবে না। অনেক দাম দিয়ে হার্ডওয়্যার কেনারও প্রয়োজন হবে না। শুধু ব্রাউজারটি খুলে একটি গেম বেছে নিয়ে প্লে বাটনে চাপ দেবেন এবং কিছু সময়ের মধ্যেই গেমটি আপনার পিসিতে চলতে শুরু করবে। যার জন্যে বিশালাকারের কোনো ফাইল ডাউনলোড কিংবা ইন্সটলেরও কোনো দরকার হবে না।

স্বপ্নের মত শোনাচ্ছে? গুগল তাদের নতুন ক্লাউড গেমিং সার্ভিসের ঘোষণা দিয়ে পৃথিবীকে এমন একটি ভবিষ্যতের কাছাকাছি নিয়ে এসেছে। তাদের দেওয়া ঘোষণা অনুযায়ী, শুধুমাত্র ক্রোম ব্রাউজার দিয়েই ফোর-কে (4K) রেজ্যুলেশনে ৬০ ফ্রেম পার সেকেন্ডে (fps) যেকোনো গেম খেলা যাবে এবং গেমগুলো আরম্ভ হতে পাঁচ সেকেন্ডের বেশি সময় নেবে না।

গত জিডিসি (গেম ডেভেলপারস কনফারেন্স) ২০১৯ সম্মেলনে গুগল তাদের ‘গুগল স্টেডিয়া’ নামে পরিচিত এই নতুন গেম স্ট্রিমিং সার্ভিসটির ঘোষণা দিয়েছে। এই প্রজেক্টটি দীর্ঘদিন থেকে ‘প্রজেক্ট স্ট্রিম’ নামে পরিচিত ছিল। স্টেডিয়ার মাধ্যমে বড় গেমগুলো চালানোর যাবতীয় জটিলতা গুগল নিজের ঘাড়ে নিয়ে নিচ্ছে। তাদের সার্ভারেই গেমগুলোর সর্বশেষ ভার্সন অনেক উচ্চ রেজ্যুলেশন আর ফ্রেম রেটে রান হবে। সেখান থেকেই গেমগুলো স্ট্রিমে এনকোড হবে এবং এরপরে ব্যবহারকারীর কাছে পাঠিয়ে দেবে। ব্যবহারকারী এরপর গেম তাদের ডেস্কটপ, ল্যাপটপ এমনকি স্মার্টফোনেও খেলতে পারবে।

সম্প্রতি ঘোষণা দেওয়া গুগল স্টেডিয়া গেমিং জগতের 'নেটফ্লিক্স' হতে চলেছে; Image Source:
কীভাবে কাজ করবে এই প্ল্যাটফর্ম? এক কথায় বলতে গেলে এটি গেমিং ইন্ডাস্ট্রির 'নেটফ্লিক্স' হতে চলেছে। এটা মূলত ক্লাউড গেমিং সার্ভিস হলেও তাতেই থেমে নেই। গেমের ডেভেলপমেন্ট থেকে অনলাইনে হোস্টিং, ব্যবহারকারীর কাছে তা পৌঁছে দেওয়া এবং একই সাথে তা প্রচারণা করা সবই এই এক প্ল্যাটফর্মে এসে একত্রিত হবে। যদিও গুগল স্টেডিয়া মুক্তি না পাওয়া পর্যন্ত বিশদভাবে কিছুই বলা যাচ্ছে না কিন্তু এই সার্ভিসটির প্রাথমিক তথ্যগুলোই এত চমকপ্রদ যে অনুমান করা হচ্ছে তা ভিডিও গেম ইন্ডাস্ট্রিতে বিশাল পরিবর্তন আনবে।

প্রাথমিক খুঁটিনাটি
স্টেডিয়ার মস্তিষ্ক হিসেবে কাজ করবে গুগল ডেটা সেন্টারের পৃথিবীব্যাপী নেটওয়ার্কটি। নেটফ্লিক্সের মতোই স্টেডিয়া তার ব্যবহারকারীদের একটা লাইব্রেরির সুবিধা দেবে যেখান থেকে তারা নিজেদের পছন্দমত গেমটি খেলা শুরু করতে পারবে। কোনো ডাউনলোড বা ইন্সটল করার প্রয়োজন হবে না। একটা সুস্থির, দ্রুতগামীর ইন্টারনেট সংযোগ এবং গুগল ক্রোম ব্রাউজারের সর্বশেষ ভার্সন থাকলেই এই সার্ভিসটি উপভোগ করতে পারবে। স্টেডিয়ার হোমপেজ অথবা ইউটিউবে নির্দিষ্ট গেমটির ভিডিও লিংক থেকেই গেমটি খেলা যাবে।


Smart City/ Green city/ SDG 11 / Debunking the smart-city myth
« on: May 28, 2019, 02:16:01 PM »
Debunking the smart-city myth

By: Adnan Zillur Morshed

I have been following the “smart city” conversation in Bangladesh for quite some time now. Last year I sat on a panel to discuss the topic during what was called the “smart-city week” in Dhaka. As Bangladesh urbanises rapidly, as mid-sized cities increasingly become its new urban frontier, the mayors of small towns across the country seem drawn to the idea of smart city. They frequently talk about how they are eager to transform their towns into smart cities. I myself spoke with a few mayors who sounded anxious to bring “smartness” to their towns.

I wondered what they actually meant. I puzzled over how they defined “smart city,” what kind of urban imageries they construed in their minds for their smart cities, what kind of life they thought people would live in their smart cities. I couldn’t help but think of the American short-story writer Raymond Carver’s anthology “What We Talk About When We Talk About Love.” What do the mayors talk about when they talk about smart cities?

I suspect that they talk about something that is not their idea, something that is not organic to their economic and cultural experiences, something that is one of the biggest hypes of our times. Do they feel pressured to jump on the smart-city bandwagon? Do they think that they would be considered backward if they didn’t talk about smart cities? I wonder whether their dream of smart city is planted in their heads by international lending agencies, multinational corporations, and real-estate organisations for marketing purposes.

I suspect most mayors see smart city as a futuristic domain of glass towers, shopping malls, apartment blocks, ICT parks, theme parks, artificial lakes, bullet trains, sleek roads, signature flyovers, a lot of neon signs, and corporate executives. Smart cities all over the world look the same, the identical technocratic glitz, the identical corporate aesthetics, the identical financial mobility. One thing is absent: the everyday life of the people.

We really can’t blame our mayors for imagining this rather faultless future of abundance and unimpeded capital flow. A swanky smart-city perception has been crystallising over the past decade or so in Bangladesh and other developing countries. The notion of smart city is often packaged with a visual language of spectacular futurism and precision. We have been told over and over again how smart city is the surefire answer to urban chaos, inefficiency, and wastefulness. And, there was a breathless impatience to accept the grand smart-city solution.   

So, what is a smart city actually? How do the pundits define it? There is no universal definition, yet its portrayal is alarmingly consistent across geographic regions. The concept of smart city is a cybernetic idea—that is, information or data can enable urban governments to establish total control over all aspects of life in the city, ranging from public transportation to electricity usage, from waste management to water supply.

This technocratic idea implies that a comprehensive system of digital infrastructures, including sensors and devices placed throughout the city, would amass a vast body of data on, among other things, people’s movement and their spatial behaviour, traffic mobility, public transportation, energy usage, utility grid, water supply, and garbage collection. The digital infrastructure would then auto-create an efficient system of energy optimisation and frictionless management. In short, smart city proposes a system of data-driven urbanisation, ensuring energy efficiency, optimal mobilisation of resources, coordinated public service delivery, and intelligent management.

IBM has been creating digital urban infrastructures that would enable city governments to consolidate all urban-service providers under a central command-and-control mechanism, eliminating all system loss. Smart-city advocates, on the other hand, hope to attract foreign investment and capital mobilisation, with a view to developing their cities as hubs of economic growth, innovation, and entrepreneurship.

These are both very inspiring and dangerous ideas. Inspiring, because everybody wants efficiency. Who wouldn’t want perfectly functioning streets with vehicles following traffic regulations and taking passengers to their destinations on time? Who wouldn’t appreciate smart street signals that auto-adjust with fluctuating traffic volume in real time? Who wouldn’t love a clean-energy utility system that lowers people’s monthly energy bill? The core idea of smart city makes sense. We should, of course, take advantage of digital infrastructures to manage urban systems and operations.

But the smart-city idea, as it is often proposed, is also dangerous. The belief that we can mitigate a city’s complex sociocultural issues with data-driven technical solutions tranquilises the very concept of the city, a place where people don’t just become a system. People also want to be free in the city. They do random things. Factory-like efficiency and big-brother digital devices in the city may stifle life and defeat the purpose of a city as a community place with its unique social characteristics and quirks. I would rather be in Kolkata than Dubai. I would rather walk on the winding medieval streets of Prague than the hyper-efficient streets of Singapore.

If the intelligence of smart city is orchestrated by software programmers, technology giants, corporate CEOs, and high priests of neoliberal capital flow, then we, the people, need to be cautious because every aspect of our lives will be programmed and monitored by these invisible power-wielders. We don’t need smart cities that only serve as neocolonial outposts, ensuring smooth capital transfer to the Wall Streets of the world, while the local glass boxes would get peanuts and false pride.

Most worryingly, the identical architecture of smart cities across the world would only ensure a new generation of corporate global domination. We must be wary of top-down mantras that reframe the city’s complex social, cultural, political, and economic issues as technical puzzles. Cities must be grounded in their unique local customs and indigenous spatial sensibilities, while also competing in the global marketplace with the strength of their future-ready aspirations and public resilience.   

This, of course, doesn’t mean that we shouldn’t use data to ensure road safety in the city; or contain dengue by pinpointing its source; or divert vehicular traffic when there is a road congestion; or create intelligent footpaths that accommodate both pedestrians and vendors. We should use digital technologies to facilitate intelligent functioning of the city.

The biggest problem with the prevailing idea of smart city is that it is woefully generic, benefitting predatory capitalism that relies on the uniformity and homogenisation of people’s lives across the world. At the heart of the smart-city hype is the misguided ideology that there is a universal technical solution to messy urban problems and unique environmental challenges. Can we get rid of urban poverty even if we have data about all aspects of the poor? It never works that way because a subject as complex as poverty can’t be quantified into a mathematical question to be answered. Instead of prematurely believing in the instant transformation of city life promised by smart cities, we should focus on an ethos of step-by-step change in the city. By centring on the public good and resilience in both urban governance and digital infrastructure discourses we can create a smart community.

Adnan Zillur Morshed is an architect, architectural historian, and urbanist. He teaches in Washington, DC, and serves as Executive Director of the Centre for Inclusive Architecture and Urbanism at BRAC University. He is an alumnus of Faujdarhat Cadet College. He can be reached at


What Are The Top 5 Major Robotics Trends To Watch In 2019?

Robots have revolutionized the manufacturing and industrial world in recent decades, and are starting to make their move into the wider world of business as well as our homes, too.

While robotic workers are now commonplace in sectors such as automobile and electronics manufacturing, 2019 should see increasingly widespread adoption across food production, retail, healthcare, and distribution operations.

So here's my rundown of some of the top predictions of where automation and robotics are set to make waves in 2019.

Robots becoming increasingly commonplace in our homes

Besides robotic vacuum cleaners, the idea of home assistance robots has been slow to take off so far. Could that change in 2019? Indeed a whole breed of startups and established companies are betting that it will. From robotic companions for the elderly to robots designed to feed, play with and care for pets while their owners are out, the apparent applications are plentiful.

The breakthrough will come when companies have gathered and analyzed real-world data on what people do, and don’t, want from robots. Robotic vacuum cleaners took off because they filled a real need, and were able to affordably carry out the duty they were designed for. Other robotic assistants – such as mobile virtual assistants – have not been so warmly received.

Promising projects which will hopefully leave the starting blocks this year include Nvidia’s collaboration with Ikea, which aims to develop the first commercially successful robotic kitchen assistant. Could 2019 be the year that tech companies finally get the recipe for domestic robots right?

Delivery robots become a reality

Robotic delivery devices are hotly tipped to solve the “last mile” problem inherent to delivery operations – the most expensive stage of the delivery process where many small, individually packaged products must be precisely targeted to reach their final destinations on time and intact.

Some of these robots are designed to work in large indoor environments – such as Segway’s Loomo robot, which carries out the delivery of internal mail in workplace settings such as office blocks and shop floors.

Others, such as Nuro, designed by a team of Google engineers, will take to the streets to deliver fresh groceries as well as hot food, thanks to its separate heated and chilled cargo bays. Nuro is already carrying out deliveries in parts of Phoenix, Arizona – a hotbed of robotic activity thanks to its grid-like streets, which are also hosting the world’s first autonomous taxis, thanks to another Google spin-off, Waymo.

Of course, there is also the delivery of parcels via airborne drone delivery – which Amazon is working on, and has already put into practice for the past year. 

More of us will work alongside robots

Collaborative robots – or cobots – are the friendly face of workplace automation – not here to steal away our jobs, but to work alongside us, providing timely advice or simply mechanical muscle at times we need it.

As robotic technology becomes more widespread and deployment costs fall, businesses will realize that they can drive efficiency by deploying robots in environments which are unsafe or inhospitable to humans. Amazon's warehouse robots are a good example – as they bring items to human workers for packaging, only comparatively small areas of their vast real estate portfolios need to be heated and made comfortable for the humans who work alongside the machines.

Collaborative robots may also provide an avenue for companies to avoid the wrathful eye of the regulators, as they look to impose punitive measures on businesses which replace humans with automation. Politicians have already proposed “robot taxes” to cover these eventualities – fostering harmonious working relationships between humans and machines could be a trend which will set people’s minds at ease in 2019.

Robots on the Edge

Robots made ideal platforms for edge computing – building sensors into the extremities of automated systems, where machines meet the real-world environments they are built to influence.

During 2019 we can expect to see advances in smart sensors – sensors with inbuilt artificial intelligence – reducing the need for information to be sent to the cloud or centralized servers for processing, before it can be acted on.

Those leading the charge include Baidu – which has just unveiled China’s first open source edge computing platform, OpenEdge, which will allow developers of robots to empower their creations with AI, reducing CPU and bandwidth overheads used by cloud infrastructure. This should enable smarter, more autonomous robots to begin to appear in homes and industrial settings throughout 2019.

The Emergence of Open Standards for Robotics

Speaking of open source – 2019 should see a consolidation of the standardization needed for AI enabled robots to achieve mass market penetration. Regulators will have a part to play here, as frameworks are put in place to govern the ways that personal data can be collected and used by autonomous machines, including self-driving cars but also autonomous home and industrial assistants.

With the legal framework offering reassurance and trust, real innovation is likely to emerge from the open source community itself – already a hotbed of robotic development and activity. Amazon recently announced the launch of its AWS Robot Maker platform, built on the open source Robotic Operating System (ROS) standards. This lowering of the entry barrier towards involvement in the development and deployment of robots should mean more organizations of all shapes and sizes stand to benefit from the robot revolution over the coming 12 months.

Thank you for reading my post. Here at LinkedIn and at Forbes I regularly write about management and technology trends. To read my future posts simply join my network here or click 'Follow'. Also feel free to connect with me via Twitter, Facebook, Instagram, Slideshare or YouTube.

About Bernard Marr

Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a strategic business & technology advisor to governments and companies. He helps organisations improve their business performance, use data more intelligently, and understand the implications of new technologies such as artificial intelligence, big data, blockchains, and the Internet of Things.

LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent contributor to the World Economic Forum and writes a regular column for Forbes. Every day Bernard actively engages his 1.5 million social media followers and shares content that reaches millions of readers.

অক্সফোর্ডের গবেষণা  : কিশোরদের ওপর সামাজিক যোগাযোগ মাধ্যমের প্রভাব ‘সামান্য’

কৈশোরকে বলা যায় অদম্য কৌতূহলের বয়স। স্বাভাবিক নিয়মেই তারা সবকিছু জানতে চায়, যার প্রভাব পড়ে তাদের জীবন ও আচরণে। ফলে কিশোর বয়সে একটি ছেলে অথবা মেয়ে চারপাশে কী দেখছে ও শুনছে তা ভীষণ গুরুত্বপূর্ণ। এ কারণেই কিশোর বয়সী সন্তানের সামাজিক যোগাযোগ মাধ্যম ব্যবহার নিয়ে অভিভাবকরা সবসময়ই উদ্বিগ্ন থাকেন। কিন্তু অক্সফোর্ড বিশ্ববিদ্যালয়ের গবেষক দল বলছে, সামাজিক যোগাযোগ মাধ্যম নিয়ে অভিভাবকদের এত বিচলিত না হলেও চলবে। কারণ কিশোর বয়সীদের জীবন সন্তুষ্টির ক্ষেত্রে এসব মাধ্যমের প্রভাব খুবই ‘সামান্য’। এর চেয়ে বরং সার্বিক আচার-আচরণে পরিবার, বন্ধু এবং স্কুলজীবন গভীর ভূমিকা রাখছে।

পিএনএস জার্নালে সম্প্রতি এ গবেষণা প্রতিবেদন প্রকাশিত হয়। যুক্তরাজ্যে বসবাসকারী ১০-১৫ বছর বয়সী ১২ হাজার কিশোর-কিশোরীর দেয়া মতামতের ওপর ভিত্তি করে গবেষণা প্রতিবেদনটি তৈরি করেছে অক্সফোর্ড। তুলনামূলক বেশি সময় ধরে সামাজিক যোগাযোগ মাধ্যম ব্যবহার করে এমন কিশোররা অধিক অসন্তুষ্টিতে ভুগছে কীনা, গবেষণায় এ প্রশ্নের উত্তর খোঁজার চেষ্টা হয়েছে। এছাড়া তরুণ প্রজন্মের ওপর প্রযুক্তির প্রভাব যাচাই করতে চেয়েছেন গবেষকরা। এজন্য সামাজিক যোগাযোগ মাধ্যমগুলো কীভাবে ব্যবহূত হচ্ছে, সে বিষয়ে তথ্য প্রকাশে কোম্পানিগুলোকে আহ্বান জানানো হয়েছে।

এর আগেও অক্সফোর্ড বিশ্ববিদ্যালয় স্ক্রিন, প্রযুক্তি ও শিশুদের মানসিক স্বাস্থ্যের মধ্যে যোগসূত্র নিয়ে গবেষণা করে। কিন্তু এ গবেষণা পরস্পর বিরোধী বলে বিতর্ক রয়েছে। অক্সফোর্ড দাবি করছে, তাদের এবারের গবেষণাটি তুলনামূলক অনেক গভীর ও গতিশীল।

অক্সফোর্ড বিশ্ববিদ্যালয়ের অক্সফোর্ড ইন্টারনেট ইনস্টিটিউটের অধ্যাপক এন্ড্রু প্রিবিস্কি বলেন, অনেক সময়ই সীমিত প্রমাণাদির ওপর ভিত্তি করে গবেষণা সম্পন্ন করা হয়, যে কারণে কোনো একটি বিষয়ে পুরোপুরি ধারণা পাওয়া যায় না।

সামাজিক যোগাযোগ মাধ্যমের ব্যবহার ও এর সঙ্গে জীবন সন্তুষ্টি কতটুকু প্রভাবিত হচ্ছে, তা বের করতেই সাম্প্রতিক গবেষণাটি সম্পন্ন হয়েছে। যেখানে বিষয় দুটির মধ্যে খুবই ‘সামান্য’ যোগসূত্র পাওয়া গেছে। গবেষণায় বলা হয়েছে, সামাজিক যোগাযোগ মাধ্যমের প্রভাব ‘একমুখী কোনো রাস্তা’ নয় এবং একজন কিশোরের আচার-আচরণ গঠনের ক্ষেত্রে তা ১ শতাংশেরও কম ভূমিকা রাখে।

অধ্যাপক প্রিবিস্কি বলেন, ‘একজন মানুষের ৯৯ দশমিক ৭৫ শতাংশ জীবন সন্তুষ্টির ক্ষেত্রেই সামাজিক যোগাযোগ মাধ্যম ব্যবহারের কোনো প্রভাব নেই।’

জরিপে অংশগ্রহণকারীদের কাছে জানতে চাওয়া হয় স্বাভাবিক স্কুলের দিনগুলোয় সামাজিক যোগাযোগ মাধ্যমের পেছনে তারা কত সময় ব্যয় করে। এছাড়া জীবনের ভিন্ন দিক নিয়ে তাদের সন্তুষ্টির পরিমাণও নির্ধারণ করা হয় প্রতিবেদনটিতে।

গবেষণায় দেখা গেছে, সামাজিক যোগাযোগ মাধ্যমে সময় কাটানোর প্রভাব তুলনামূলক কিশোরীদের ক্ষেত্রে বেশি। অবশ্য এ প্রভাবও খুব সামান্য। আর কিশোরদের ওপর বড় ধরনের কোনো প্রভাব পাওয়া যায়নি। এ অবস্থায় সন্তানের সামাজিক যোগাযোগ মাধ্যমে সময় কাটানো নিয়ে মা-বাবার উদ্বিগ্ন হওয়ার প্রয়োজন নেই বলে জানিয়েছেন অধ্যাপক প্রিবিস্কি।

তবে সামাজিক যোগাযোগ মাধ্যমের নির্দিষ্ট কিছু প্রভাবে ঝুঁকিগ্রস্ত তরুণদের চিহ্নিত করাই এখন সবচেয়ে গুরুত্বপূর্ণ কাজ বলে মনে করেন তারা। কোন কোন বিষয় কিশোরদের আচার-আচরণে প্রভাব ফেলছে, সেটিও খুঁজে বের করার প্রতি জোর দেন তিনি।


পুরনো স্মার্টফোনের ব্যবহার...
বিশ্বের প্রায় প্রত্যেক মানুষ পকেটে ছোট একটি সুপারকম্পিউটার বহন করছে, যা ব্যবহার করে আবহাওয়ার পূর্বাভাস দেখে নেয়া, গেম খেলা, মিডিয়া কনটেন্ট স্ট্রিম করা, ছবি ধারণ কিংবা ডাটা বিশ্লেষণের মতো কাজ অনায়াসে করা যাচ্ছে। আধুনিক প্রযুক্তির দারুণ একটি অনুষঙ্গ স্মার্টফোন। ক্রমবর্ধমান চাহিদার কারণে প্রতিনিয়ত উন্নত হচ্ছে স্মার্টফোন ডিভাইস। এতে পুরনো স্মার্টফোন ফেলে নতুন কেনার আগ্রহ দেখা যায় গ্রাহক পর্যায়ে। এক পর্যায়ে পুরনো স্মার্টফোন ফেলে রাখা হয় বাসাবাড়ির যত্রতত্র। তবে পুরনো স্মার্টফোনের ওয়াই-ফাই সংযোগ সচল থাকলে তা ফেলে না রেখে নানা কাজে লাগানো যায়। পুরনো স্মার্টফোন যেসব কাজে লাগানো যেতে পারে তা নিয়ে আয়োজনের আজ পর্ব—

ওয়্যারলেস রাউটার

বেশির ভাগ স্মার্টফোনেই বিল্টইন ওয়াই-ফাই হটস্পট ফিচার থাকে। এ ফিচার থাকলে আপনি সহজে পুরনো স্মার্টফোনটিকে পোর্টেবল রাউটার হিসেবে ব্যবহার করতে পারবেন। থ্রিজি সিম কার্ড দিয়ে এ সুবিধা নেয়া যাবে। পকেট ওয়াই-ফাই হিসেবে পুরনো স্মার্টফোন ব্যবহারের ফলে ইন্টারনেট সমর্থিত প্রত্যেকটি পণ্যে আলাদা সংযোগ নেয়ার প্রয়োজন হবে না। কাজেই পুরনো স্মার্টফোন ফেলে না রেখে নিরাপদ অ্যাকসেস পাসওয়ার্ড ব্যবহার করে ওয়াই-ফাই হটস্পট তৈরি করে নিতে পারেন নিজেই।

অ্যাপ্লিকেশন পরীক্ষা

অ্যান্ড্রয়েড ও আইওএসের পাশাপাশি উইন্ডোজ প্লাটফর্মের অ্যাপ্লিকেশন বাড়ছে। বিভিন্ন অ্যাপ্লিকেশন পরীক্ষা করে দেখার জন্য পুরনো স্মার্টফোন কাজে লাগানো যেতে পারে। নতুন স্মার্টফোনে প্রয়োজনীয় কোনো অ্যাপ্লিকেশন ইনস্টল করার আগে তা পুরনো স্মার্টফোনে পরীক্ষা করে দেখে নিলে নানা রকম ঝামেলা থেকে মুক্তি মিলতে পারে। এছাড়া অপ্রয়োজনীয় বোল্টওয়্যার বা অ্যানিমেশন ইফেক্ট সরিয়ে মোবাইলের ব্যাটারির আয়ু বাড়াতে কাস্টম রম পরীক্ষায় কাজে লাগানো যায় পুরনো স্মার্টফোন।

টিভির মিডিয়া প্লেয়ার

পুরনো স্মার্টফোনে টিভি-আউট বা এইচডিএমআই আউটপুট ফিচার থাকলে তা ফ্ল্যাশভিত্তিক মিডিয়া প্লেয়ার হিসেবে ব্যবহার করা যাবে। এজন্য ডিভাইসটিতে ৩২ কিংবা ৬৪ গিগাবাইট অভ্যন্তরীণ স্টোরেজ সুবিধার হতে হবে। ডিভাইস স্টোরেজে থাকা মুভি ও ভিডিও হাই ডেফিনেশন লিংক (এমএইচএল) বা এইচডিএমআই কেবল দিয়ে টিভির সঙ্গে সংযোগ স্থাপন করে বড় পর্দায় দেখা যাবে। ডিভাইসটি ডিএলএনএ বা মিরাকাস্ট নামের পিয়ার-টু-পিয়ার ওয়্যারলেস স্ক্রিনকাস্টিং সমর্থন করলে ওয়্যারলেস উপায়ে স্টোরেজে থাকা মাল্টিমিডিয়া অন্য ডিভাইসে সম্প্রচার করা যাবে।

ওয়্যারলেস সিকিউরিটি ক্যামেরা

পুরনো অব্যবহূত স্মার্টফোনকে ওয়্যারলেস সিকিউরিটি ক্যামেরা হিসেবে রূপান্তর করা যেতে পারে। অ্যান্ড্রয়েড কিংবা আইওএস প্লাটফর্মে এ ধরনের অসংখ্য অ্যাপ্লিকেশন পাওয়া যায়। অ্যান্ড্রয়েডের জন্য আইপি ওয়েবক্যাম, আইওএসের জন্য আইভিজিলো স্মার্টক্যাম কাজে আসতে পারে। এ অ্যাপ্লিকেশনগুলো স্মার্টফোনের ক্যামেরার সাহায্যে লাইভ ভিডিও স্ট্রিমিং করতে পারে, যা অন্য কোনো স্ট্রিমিং সমর্থিত পণ্যের যেকোনো ব্রাউজারে বা ভিডিও প্লেয়ারে দেখা যায়। স্ট্রিমিং অ্যাপ্লিকেশন ইনস্টল করা থাকলে এবং ওয়াই-ফাই নেটওয়ার্কের মধ্যে থাকলে পুরনো স্মার্টফোন ডিভাইস ওয়্যারলেস সিকিউরিটি ক্যামেরার কাজ করবে।

জিপিএস নেভিগেটর

অ্যান্ড্রয়েড ফোনে গুগল ম্যাপস ও নেভিগেশন বিনা মূল্যেই পাওয়া যায়। গাড়ি চালানো কিংবা অপরিচিত কোনো স্থানে এ নেভিগেশন ব্যবহার করে সহজে পথ চিনে নেয়া যাবে। অর্থাৎ পুরনো স্মার্টফোনটি যদি অ্যান্ড্রয়েড-চালিত হয়, তবে গাড়ির জন্য আলাদা করে জিপিএস নেভিগেটর কেনার দরকার হবে না। পুরনো স্মার্টফোন গাড়িতে নেভিগেশন করার জন্য স্থায়ীভাবে রেখে দেয়া যেতে পারে। এজন্য জেনেরিক মাইক্রো ইউএসবি ১২ ভোল্ট কার চার্জার দরকার হবে, যা মোবাইল ফোনটিকে চার্জ দিতে কাজে লাগবে। কার ড্যাশবোর্ড নামে একটি অ্যাপ্লিকেশন ইনস্টল করে নিলে এবং প্রয়োজনমতো কাস্টমাইজ করে নিলে পুরনো স্মার্টফোনকে কার নেভিগেটর হিসেবে ব্যবহার করা যাবে।

পিসির রিমোট কন্ট্রোলার

পুরনো স্মার্টফোনকে টিভি কিংবা এসির পাশাপাশি পিসির রিমোট কন্ট্রোলার হিসেবেও ব্যবহার করা যাবে। পিসির কন্ট্রোলার হিসেবে ওয়্যারলেস মাউস সবচেয়ে সুবিধার হলেও, যদি দূরে সোফা বা চেয়ারে বসে কম্পিউটার চালানোর প্রয়োজন হয়, তখন পুরনো স্মার্টফোনটিকে কন্ট্রোলার হিসেবে কাজে লাগানো যেতে পারে। কম্পিউটারের ব্রাউজিং বা কোনো ভিডিও যদি বড় স্ক্রিনে দেখতে চান, তবে পুরনো স্মার্টফোন কাজে লাগানো যাবে। বিনা মূল্যের অ্যাপ্লিকেশন ‘মোবাইল মাউস লাইট’ এক্ষেত্রে কাজে লাগানো যেতে পারে। পুরনো স্মার্টফোন পিসির রিমোট হিসেবে ব্যবহার করতে মোবাইল ও পিসি উভয় ডিভাইসই একই ওয়াই-ফাই নেটওয়ার্কে থাকতে হবে। সূত্র: পিসিম্যাগ

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চাই না মানুষ ফোনে আসক্ত হয়ে পড়ুক: টিম কুক

স্মার্টফোনে আসক্তি এখন একটি বড় সমস্যা হয়ে দেখা দিয়েছে। এর ভয়াবহতা পরিবার কিংবা সামাজিক পরিসর ছাড়িয়ে কর্মক্ষেত্রেও সমস্যা হয়ে উঠেছে। ব্যক্তিজীবনে তো বটেই, বন্ধুদের সঙ্গে আড্ডা কিংবা গুরুত্বপূর্ণ কাজের আলাপচারিতার সময়ও কারো কারো চোখ পড়ে থাকে স্মার্টফোনে! চারপাশে কী হচ্ছে, সেসবে যেন খেয়াল করেন না তারা। সম্প্রতি নিউইয়র্কে অনুষ্ঠিত ‘টাইম ১০০ সামিট’-এ নিয়ন্ত্রণ ও রাজনৈতিক অনুদানসহ বিভিন্ন বিষয়ে কথা বলেন অ্যাপলের প্রধান নির্বাহী কর্মকর্তা (সিইও) টিম কুক। এ সামিটেই তিনি বলেন, আমরা চাই না মানুষ সার্বক্ষণিক বা আসক্ত হয়ে ফোন ব্যবহার করুক। খবর ম্যাশেবল।

হাসিমুখে টিম কুকের এমন বক্তব্যের আড়ালে অনেকে তার চৌকস বুদ্ধিমত্তার বহিঃপ্রকাশ দেখছেন। অনেকে বলছেন, অবশ্যই তিনি চৌকস বুদ্ধিসম্পন্ন একজন সিইও। তবে তিনি যা-ই করুন বা বলুন না কেন, এর পেছনে ব্যবসায়িক উদ্দেশ্য আছে নিশ্চয়। তিনি সামিটে গোপনীয়তা ও ডিজিটাল ডিভাইসের স্ক্রিন টাইম বিষয়ে অ্যাপল অন্য প্রযুক্তি প্রতিষ্ঠান থেকে কীভাবে আলাদা, সে বিষয়ে কথা বলেন।

টিম কুক বলেন, বিশ্বব্যাপী স্মার্টফোনের ব্যবহার বাড়ছে। দৈনিক জীবনের অনেক গুরুত্বপূর্ণ কাজ সহজ করেছে স্মার্টফোন। এ ডিজিটাল অনুষঙ্গের নেতিবাচক দিক হলো, অনেক মানুষ আসক্ত হয়ে পড়েছে। আমরা চাই না মানুষ আসক্ত হয়ে স্মার্টফোন ব্যবহার করুক। এটা আমাদের উদ্দেশ্য না।

তিনি দাবি করেন, অ্যাপল ডিভাইসে বেশি সময় কাটানোর জন্য মানুষকে চাপ প্রয়োগ করা আমাদের উদ্দেশ্য না। টিম কুক আক্ষেপ করে বলেন, মানুষের ডিজিটাল ডিভাইসে স্ক্রিন টাইম নিয়ে নিয়মিত হাজার হাজার নোটিফিকেশন পাই। ডিজিটাল ডিভাইসে মানুষ এতটাই আসক্ত হয়ে পড়েছে যে অন্য মানুষের চেহারার দিকে তাকানোরও সময় নেই অনেকের। এটা সত্যি উদ্বেগের বিষয়।

টিম কুক বলেন, আমরা কোনোভাবেই মানুষের স্ক্রিন টাইম বাড়ানোর পক্ষে নই। ব্যবসার দিক বিবেচনায় আমরা ডিজিটাল স্ক্রিনে আরো বেশি সময় কাটানোর জন্য মানুষকে উৎসাহিত করতে পারি না। এছাড়া স্ক্রিন টাইম বাড়লেও আমাদের ব্যবসায় তা বাড়তি যোগ্যতা যোগ করবে না।

বিশ্লেষকদের মতে, ডিজিটাল স্ক্রিন টাইম নিয়ে অ্যাপল সিইওর বক্তব্য স্পষ্ট এবং বেশ উচ্চমার্গীয়। তবে অ্যাপল আইফোনের মতো জনপ্রিয় ডিভাইস এবং সংশ্লিষ্ট ইকোসিস্টেমের উদ্ভাবক। অথচ এ ধরনের ডিভাইসকেন্দ্রিক নোটিফিকেশন অপছন্দ করেন টিম কুক। সত্যিকার অর্থে এখনো আইফোন এবং আইফোনকেন্দ্রিক সংশ্লিষ্ট সেবা ইকোসিস্টেম থেকে অ্যাপলের রাজস্বের সিংহভাগ আসছে। অ্যাপ ক্রয় এবং ইন-অ্যাপ পেমেন্ট খাত থেকে বিপুল অর্থ উপার্জন করছে অ্যাপল। ২০১৮ সালে সেবা খাত থেকে অ্যাপলের রাজস্ব আয় এক বছর আগের চেয়ে ২৪ শতাংশ বেড়ে ৩ হাজার ৭২০ কোটি ডলারে পৌঁছেছে।

টিম কুক তার বক্তব্যে জানিয়েছেন, ডিজিটাল ডিভাইসে অর্থবহ এবং ক্ষমতায়নে সহায়তা করে, এমন সময় ব্যয় করুন। অর্থাৎ নিজেকে সমৃদ্ধ করে ততটুকু সময় ডিভাইস স্ক্রিনে ব্যয় করা উচিত। বাকি সময় অন্য মানুষের সঙ্গে কাটান, যা মানুষের সঙ্গে মানুষের সম্পৃক্ততা বাড়াবে।

ডিভাইস নির্মাতাদের জন্য স্মার্টফোন আসক্তি মাথাব্যথার কারণ হয়ে উঠেছে। এ নিয়ে বিভিন্ন ধরনের সমালোচনা সামাল দিতে হচ্ছে। স্ক্রিন টাইম বিষয়ে বাকি ডিভাইস নির্মাতাদের চেয়ে অ্যাপলের উদ্যোগ এরই মধ্যে প্রশংসা কুড়িয়েছে। মার্কিন প্রযুক্তি প্রতিষ্ঠানটি তাদের নতুন ডিভাইসগুলোতে স্ক্রিন টাইম কমানোর লক্ষ্যে একাধিক ফিচার এনেছে।


QA Mechanism / Creating a generation of learners and innovators
« on: May 04, 2019, 01:49:37 PM »
Creating a generation of learners and innovators

The curriculum for any undergraduate programme is highly influenced by the social, physical, economic and cultural environment. Consequently, with the change of any such setting(s), its development process will also change. The great economist and Nobel Laureate, Wassily Leontief, wrote in 1953 that “labour will become less and less important… More and more workers will be replaced by machines.”

However, an insightful way to understand the overall effect of new technology on the number of jobs in the economy is to look at it as a race between two dynamic processes. Automation tends to take jobs away while the invention of new complex tasks creates new jobs. In this context, there is an increasing demand for graduates who can speak and write effectively, have high-quality interpersonal (teamwork) and creative thinking skills, are innovative and have some understanding of world affairs, and can work effectively with individuals from different cultures and backgrounds. Universities in developed countries as well as in many developing countries are paying greater attention to the quality of education they provide to students, and to redesigning curricula. These institutions are constantly rethinking their goals and priorities, their curricula, and the way learning takes place.

The present curriculum development process is different from that of traditional curriculum development. In the traditional process, the curriculum is a collaborative effort of senior faculty members and course teachers. Course teachers are involved as they know the contents of the courses and the way courses are taught. The curriculum focuses on a specific body of knowledge to be transmitted to students and relies heavily on memorisation and drilling of facts and formulas. Education systems founded on traditional curricula often focus solely on the subject matter being taught and favour measurement of educational objectives via a great deal of testing. Statements of programme outcomes do not exist for curricula and courses. Traditionally, course improvement has been the responsibility of individual faculty, and efforts to redesign curricula have usually been assigned to departmental committees established specifically for this purpose.

Designing a quality course or curriculum is always difficult, time-consuming, and challenging. A curriculum must be developed sequentially, beginning with aligning programme educational objectives with the institutional statement of vision and ending with the assessment of each student before and after graduation. It requires thinking about programme educational objectives and programme outcomes for students, the demands of accreditation agencies, competencies and skills required at jobs, and how a teacher can facilitate the learning process.

Programme educational objectives are broad statements that describe the career and professional accomplishments of graduates. Keep in mind that although programme educational objectives are long-range and focused on performance well after graduation, it is possible within an undergraduate programme to identify the skills, attitudes, and understandings that are the underpinnings of these long-range objectives. On the other hand, programme outcomes must be achieved during the academic programme. Each programme must have documented student outcomes that prepare graduates to attain the programme educational objectives.

As the design process starts, from defining programme educational objectives to developing programme outcomes and course outcomes and then course-by-course outcomes, the statements become increasingly specific. The design of each course, the selection of instructional methods, and student assessment are based on these statements. The process of moving from a statement of objectives and outcomes to deciding on and implementing a programme and relating individual courses to the curriculum requires careful planning. If, for example, speaking skills are identified as a basic competency that every student must have by graduation, public speaking must be initially taught and then reinforced, and no student should be able to graduate without receiving appropriate instruction and practice in this skill. Courses must be analysed to identify where this skill is introduced and then reinforced, and the curriculum must be structured so that every student has the opportunity to acquire speaking skills. In the case of developing competencies in speaking, the required courses will most likely be those with smaller enrolment, or lecture courses that have discussion sessions associated with them. Developing and using interpersonal skills, problem-solving, critical thinking, basic statistics, and so on, are widely listed core objectives and can be an integral part of most courses.

In every institution, the final determinant of the quality of the academic programme is the performance of its graduates. The degree of success will depend on how well the curriculum is delivered through its courses and other learning experiences provided to students. Every student must have the opportunity to reach and demonstrate every stated basic competency. Carefully articulated learning outcomes must be the basis on which instructional methods are chosen and the criteria by which competency must be measured. The effectiveness of an institution or programme and of individual faculty members is then determined by the ability of students to meet these objectives and outcomes. At the same time, it must be recognised that not all students will reach these goals, because their attitudes, willingness to work, and ability also play an important role in determining success. It is the responsibility of an institution to do everything to facilitate the learning that is required and to give each student a fair opportunity to succeed.

Higher education generates broader economic growth as well as individual success. For example, a recent study determined that universities contributed nearly 60 billion pounds to the economy of the United Kingdom in 2007-08 (Drew Gilpin Faust, June 30, 2010). Therefore, universities in Bangladesh can also change the society and remain the centre of change and economic development. In that case, universities need to produce graduates with high-level skills, critical thinking competency and innovative quality; and such graduates can get jobs in national and global markets, and also can be successful as entrepreneurs and self-employed workforce. Such dispositions demand changes in curricula, and teaching and assessment methods to create a young generation of active learners and creators. The primary task lies with universities in Bangladesh to develop curricula for programmes following the widely accepted development process.

MM Shahidul Hassan is Vice Chancellor of East West University, Dhaka. Email:


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