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চার দশক আগেই মঙ্গলে প্রাণের অস্তিত্ব পায় নাসা

সৌরজগতের লোহিত গ্রহ মঙ্গল নিয়ে গবেষণা চলছে যুগ যুগ ধরে। সেখানে প্রাণের অস্তিত্ব রয়েছে কি না, গ্রহটি মানুষের দ্বিতীয় আবাস হতে পারবে কি না—এসব প্রশ্নের উত্তর বিজ্ঞানীরা খুঁজে চলেছেন প্রতিনিয়ত। কিন্তু যুক্তরাষ্ট্রের মহাকাশ গবেষণা সংস্থার (নাসা) সাবেক এক বিজ্ঞানী দাবি করেছেন, চার দশক আগেই মঙ্গলে প্রাণের অস্তিত্ব পেয়েছিলেন তাঁরা। কিন্তু নাসা সে সময় তা আমলে নেয়নি।

নাসা ১৯৭৬ সালে মঙ্গলে প্রাণের অস্তিত্ব অনুসন্ধানে ভাইকিং অভিযান পরিচালনা করে। মহাকাশযানটির একটি অংশ কক্ষপথ থেকে মঙ্গলপৃষ্ঠের ছবি তুলেছে। অপর অংশটি মঙ্গলপৃষ্ঠে অবতরণ করে প্রাণের অস্তিত্ব অনুসন্ধান করেছে। অংশটির নাম ছিল ভাইকিং ল্যান্ডার। আর অনুসন্ধান অভিযানের নাম দেওয়া হয়েছিল লেবেলড রিলিজ, সংক্ষেপে এলআর। নিয়ন্ত্রণকক্ষে এলআরের নেতৃত্বে ছিলেন নাসার প্রকৌশলী ও উদ্ভাবক গিলবার্ট ভি লেভিন। তিনিই গত বৃহস্পতিবার যুক্তরাষ্ট্রের জনপ্রিয় বিজ্ঞান সাময়িকী সায়েন্টিফিক আমেরিকান–এ ওই অভিযানের পাওয়া ফলাফল নিয়ে একটি দীর্ঘ নিবন্ধ লিখেছেন।




নিবন্ধে গিলবার্ট লেখেন, ‘১৯৭৬ সালের ৩০ জুলাই মঙ্গলপৃষ্ঠ থেকে এলআর তার প্রাথমিক অনুসন্ধানের তথ্য পাঠায়। ফলাফল ছিল আশ্চর্যকরভাবে ইতিবাচক। আমরা ইঙ্গিত পেয়েছিলাম, লোহিত গ্রহটিতে আণুবীক্ষণিক জীব রয়েছে। ওই সব জীবের শ্বাসপ্রশ্বাসের আভাস পেয়েছিলাম আমরা। পৃথিবীর মাটিতে প্রাণের অস্তিত্ব অনুসন্ধানের পরীক্ষায় এলআর থেকে যে ধরনের তথ্য আমরা পেয়েছিলাম, মঙ্গলপৃষ্ঠ থেকে পাঠানো তথ্যের সঙ্গে তা অনেকাংশেই মিলে যায়। এর অর্থ হলো, আমরা চূড়ান্ত জবাব পেয়ে গিয়েছিলাম।’

কিন্তু নাসা উপসংহারে পৌঁছায়, মঙ্গলে এলআর যা পেয়েছে, তা প্রাণের অস্তিত্বের মতো হলেও সরাসরি প্রাণ নয়। গিলবার্টের ভাষায়, নাসা ওই ফলাফল আমলেই নেয়নি। অথচ ভাইকিং অভিযানে মঙ্গলে প্রকৃত অর্থেই প্রাণের অস্তিত্ব পাওয়া গিয়েছিল।

এর আগে গত ফেব্রুয়ারিতে নাসার প্রশাসক জিম ব্রাইডেনস্টাইন বলেন, মঙ্গলে আণুবীক্ষণিক জীবের অস্তিত্ব থাকলেও থাকতে পারে। লোহিত গ্রহটিতে মহাকাশচারী পাঠাতে যুক্তরাষ্ট্র প্রতিশ্রুতিবদ্ধ। তথ্যসূত্র: ইনডিপেনডেন্ট

Web source: https://www.prothomalo.com/technology/article/1619518/%E0%A6%9A%E0%A6%BE%E0%A6%B0-%E0%A6%A6%E0%A6%B6%E0%A6%95-%E0%A6%86%E0%A6%97%E0%A7%87%E0%A6%87-%E0%A6%AE%E0%A6%99%E0%A7%8D%E0%A6%97%E0%A6%B2%E0%A7%87-%E0%A6%AA%E0%A7%8D%E0%A6%B0%E0%A6%BE%E0%A6%A3%E0%A7%87%E0%A6%B0-%E0%A6%85%E0%A6%B8%E0%A7%8D%E0%A6%A4%E0%A6%BF%E0%A6%A4%E0%A7%8D%E0%A6%AC-%E0%A6%AA%E0%A6%BE%E0%A7%9F-%E0%A6%A8%E0%A6%BE%E0%A6%B8%E0%A6%BE?fbclid=IwAR137ZI9EeZazErbJD6spOzvpAYAXMtcGBVT4gSH7aktYVM9Td9iIPHycYE


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Most Popular Programming Languages 1965 - 2019

Source: https://www.youtube.com/watch?v=Og847HVwRSI

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News & Events / IQAC Newsletter: Volume 2: Issue 1
« on: October 17, 2019, 04:14:06 PM »

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Higher Education and Emerging Technologies / WHAT IS UNIVERSITY 20.35
« on: October 17, 2019, 01:08:37 PM »
WHAT IS UNIVERSITY 20.35

University 20.35 is the first university in Russia providing opportunities for professional development by creating individual educational trajectories and tracking digital skill profiles.
It is aimed at training business leaders, participants of the National Technology Initiative and professionals entering new global markets.University 20.35 pioneers a new network-based learning principle, where educational trajectories for each  student are selected in a personalized manner. Different universities, online education platforms and other organizations are providing this customized content. Students are trained both offline and online through the digital platform of the University.
University 20.35 was established by the Agency for Strategic Initiatives (ASI) to promote new projects. Partners: Skoltech, Innopolis, ITMO, SPbPU, MIPT, Novosibirsk State University, Tomsk State University, Far Eastern Federal University.

UNIQUE FEATURES OF UNIVERSITY 20.35

01 Recommendations for personal education trajectories based on the results of the students’ current skill diagnostics, educational background and individual needs.
02 Combination of online and offline learning from world-class teachers with top level skills.
03 Community of the National Technology Initiative leaders and the possibility to study together.
04 Digital skills profile.
05 Recommendations on team development (considering each participant’s profile) for technological projects.

RESEARCH
University 20.35 pioneers a new university model, where each student at any given moment makes a decision on his/her further educational steps based on recommendations that take into account the student's digital footprint, digital footprints of other students, and the educational content and activities available.

The recommendations include:
the choice of professional activity;
a list of the skills and knowledge that are necessary for this professional activity;
a selection of events, courses, educational methods, scholarly endeavors and professional activities that will ensure the student's development.

University 20.35 joins efforts with leading academia institutions to facilitate transition towards network-based education.

University holds pilot programs at selected Russian universities offering students an opportunity to develop a set of competencies required for digital economy via personalized blended learning curves. Educational content providers, proffering unique learning experiences related to digital economy are encouraged to share their content at University 20.35's platform.

Therefore, new students get a unique opportunity to build personal educational paths from the variety of available modules.


Source: https://2035.university/en/

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Is Artificial Intelligence the Ultimate University Stimulus?

What does it take to make the university the best learning experience in the lifecycle of one’s education? Higher education is all about developing skills, exploring new theories, and applying them to the actualities of real life. Throughout this journey, students are encouraged to stay on top of their workload, study, and complete assessments all while simultaneously leading a healthy, active, and balanced social life.

Existing Fractures in the University Structure

The essential materials relied on at university include books, books, and more books. As we move into an age of digitalization of practically everything, there is a reason to believe that the existing higher education model should too be digitalized to allow for an enhanced university experience.

The existing model of higher education looks something along the following lines.
Based on a one-module-fits-all curriculum, where students are all expected to learn the same thing in the confines of a classroom, they will then be assessed by examinations based on rigid criteria to determine a pass or fail. These intrinsic features of the education system do little to contribute to an enhanced learning experience. Instead, prospects for development under the current model seems to have come to a halt.

The world around us moves closer to an entirely digitalized world.

Having the entire world become digitalized is essential as little else could be more detrimental to the future than our young minds being taught in obsolete ways. Artificial intelligence has disrupted almost every industry. The AI market is expected to generate $3 trillion in revenue by 2024.



Based on a 2018 report assessing the expected impact of AI and machine learning on a selection of domains worldwide, only 3% of respondents believed that AI would not affect society in general within two years (Statista).

The ability of intelligent machines to perform highly sophisticated and specific tasks without explicit human input should not be overlooked in the higher education sector.

Artificial Intelligence Technological Solutions

AI’s ability to make recommendations and produce answers based on patterns and inferences is precisely what humans cannot do on a mass scale – and precisely what our existing university structure demands.

University 20.35, (https://2035.university/en/), introduces the first university model that provides opportunities for professional development by creating individual educational trajectories and tracking digital skill profiles using artificial intelligence.

The use of digital footprints, which the platform collects during educational processes measures and analyses the students’ skills. Then, it confirms or refutes whether a trajectory module teacher can efficiently transfer skills to the students.

University Model

The network of organizations and digital platforms.
The use of AI here is of great revelation. It’s currently being implemented in personal educational trajectories development. In other words, the collection of Big Data on a student’s educational and professional background, combined with his/her digital footprint allows the intelligent machine to suggest the best development path.

A large part of university learning takes place within labs and lecture theatres.
If there’s one thing that makes studying at university better, it has everything you need to learn, study, and research wherever the student may be. Whether studying, learning or research takes place on the go or from home can be the students’ choice.  Through a combination of online and offline education, artificial intelligence allows students to study where and when they want.

Using whichever platform they prefer or need, makes learning more accessible to everyone. The learning, in turn, lends to the prospects of AI for future students. It may mean that the use of mobile devices and online data collection increases.

This shift way from popular book learning towards smart devices contributes to the mass data we collect as a population. More data essentially means more information and better AI developed models.

We think of the most enhanced environments for learning.
We might conjure up images in our heads of groups of students studying together, in an attempt to improve their existing skills and fill in the gaps in their knowledge. Before the introduction of AI, this image of students was the only one conceivable, but it’s not the most effective.

AI, through the collection and analysis of digital footprints, allows for the creation of each students’ digital twin. Digital twins are essentially the digital replica of physical assets, i.e., the physical twin or the replica is of the student.

This accurate and near to real-time data based on digital footprint as well as some biological data can help to establish better solutions for students. This includes the biological of the surroundings as well as personal biolgical data. The application of the digital twin in higher education has the potential to shed light on gaps in the student’s knowledge, their forgetfulness, and hone in on their strengths.

Through AI, digital twins can materialize into a functional and personal study buddy.
Twinning is effectively a solid starting point for the development of a proactive educational study plan. From here, as the data reflects the student’s actual profile, the near to real-time data of the students’ progress will represent the students’ knowledge and skills.

Twinning can also be modeled to take into account what the student forgets and the skills they are practicing. The digital economy awaits, and as things stand, the next generation of our workforce have been and continue to be, educated and trained in an educational model that is incompatible with the digital future.

The university project, Island 10-22, is an incentive for education leaders aimed at intensive skills development specifically for the digital economy.
Participants of this project receive skills development in the field of digital and cross-cutting technologies. They are therefore anticipated to be the most sought after members of the labor market and will lead in the transition into a digital global economy.

“We aim to create a flexible digital education system, not even of tomorrow, but for the day after, based on the unique Russian educational AI.”The Russian education AI will enable quick training of these specialists and teams to solve complex problems,” said Dmitry Peskov, head of University 20.35.

On many occasions, students at university will be expected to work in groups on team projects.
Artificial intelligence technologies can make intelligent recommendations on team development for technical projects. And nothing enhances learning quite like team development. Collaboration drives innovation. Artificial intelligence, by considering each participant’s profile, we can assemble the most efficient teams and distribute work according to skill and proficiency.

AI poses some strategic and educational revolutionary technical solutions.
Each of these can help the current educational model reach the next milestone in maximizing both its standards and the level of expertise in students it produces. Total digital footprint recording allows AI to analyze the interaction of the participants in social networks.

The results of completed tasks, geolocation, as well as uploads of videos and photos, make possible a personalized program based on the needs of the student. Subsequently, individual development pathways with AI assistants can be created for each student.

When looking ahead at development records and tracing the students’ progress, AI, through semantic speech analysis allows the tracking of changes in the participants’ mindsets. Biometric data gathering can identify stress and fatigue levels to analyze different stages of the program. This data can then be used to modify the program accordingly.

AI puts students on a personal development pathway based on their digital footprints.
AI can do much more than condense a lecture into flashcards and smart online study guides. It has thus far, automated administrative tasks, introduced personalized learning to the extraordinarily generic syllabus that exists today.

AI’s application is still in its early stages; its continued development will soon see it working as a full-fledged AI-based university model. The model will be immersed entirely on the premise of machine learning and artificial intelligence. Simultaneously, its development will generate a higher caliber of students.

Source: https://readwrite.com/2019/10/10/is-artificial-intelligence-the-ultimate-university-stimulus/

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Emerging Technologies / Web link of IFZ-FinTech study 2019
« on: October 16, 2019, 02:26:31 PM »
Web link of IFZ-FinTech study 2019

IFZ FinTech Study 2019 analyses both global FinTech companies and the Swiss FinTech sector. The fourth edition of the IFZ-FinTech study aims to show the developments in the FinTech in 2018 and to re-evaluate the trends observed in previous studies. FinTech companies are increasingly becoming an integral part of the financial services industry. By the end of 2018, there were 356 Swiss FinTech companies, representing an increase of 62% from 220 companies one year earlier. The study shows that 122 companies are active in the field of Distributed Ledger Technology, 66 – in Investment Management, 56 – in Banking Infrastructure, 42 – in Deposit & Lending, 36 – in Payment, and 34 – in Analytics.



To study more on the report (IFZ-FinTech study 2019), you may kindly download from the below web link:

https://blog.hslu.ch/retailbanking/files/2019/03/IFZ-FinTech-Study-2019_Switzerland.pdf

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Economics and Business Studies / Web link of IFZ-FinTech study 2019
« on: October 16, 2019, 02:20:47 PM »
Web link of IFZ-FinTech study 2019

IFZ FinTech Study 2019 analyses both global FinTech companies and the Swiss FinTech sector. The fourth edition of the IFZ-FinTech study aims to show the developments in the FinTech in 2018 and to re-evaluate the trends observed in previous studies. FinTech companies are increasingly becoming an integral part of the financial services industry. By the end of 2018, there were 356 Swiss FinTech companies, representing an increase of 62% from 220 companies one year earlier. The study shows that 122 companies are active in the field of Distributed Ledger Technology, 66 – in Investment Management, 56 – in Banking Infrastructure, 42 – in Deposit & Lending, 36 – in Payment, and 34 – in Analytics.



To study more on the report (IFZ-FinTech study 2019), you may kindly download from the below web link:

https://blog.hslu.ch/retailbanking/files/2019/03/IFZ-FinTech-Study-2019_Switzerland.pdf


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Workshop on 'Class Monitoring Mechanism', organized by IQAC, DIU

To discuss the details of ToR of Classroom Monitoring Mechanism, IQAC, DIU is going to arrange a workshop (on 14 October, 2019) where Director, IQAC, DIU will brief you on how to use the ToR for monitoring classroom. Honorable Vice Chancellor, DIU will grace the occasion as Chief Guest' and he will give you proper directions on this issue.

The programme matrix is as follows:

Date: 14 October, 2019
Day: Monday
Time: 3:30 p.m. to 5:00 p.m.
Venue: Room 308, Main Campus of DIU, 102, Shukrabad, Dhanmondi, Mirpur Road, Dhaka

9
Workshop on 'Class Monitoring Mechanism', organized by IQAC, DIU

To discuss the details of ToR of Classroom Monitoring Mechanism, IQAC, DIU is going to arrange a workshop (on 14 October, 2019) where Director, IQAC, DIU will brief you on how to use the ToR for monitoring classroom. Honorable Vice Chancellor, DIU will grace the occasion as Chief Guest' and he will give you proper directions on this issue.

The programme matrix is as follows:

Date: 14 October, 2019
Day: Monday
Time: 3:30 p.m. to 5:00 p.m.
Venue: Room 308, Main Campus of DIU, 102, Shukrabad, Dhanmondi, Mirpur Road, Dhaka

10
Employability / How will the future employee looks?
« on: October 14, 2019, 12:24:29 PM »
How will the future employee looks?

Professor Ujjwal K Chowdhury

The past employees worked 9 to 5 in a corporate office, using company equipment, remaining focused on inputs with a pre-defined work and wanting to climb the corporate ladder

Jacob Morgan categorically defines the principles and characteristics of the future employee, future manager and future organizations, which are relevant for India too.
The seven principles of the future employee include: has a flexible work environment, can customize own work, shares information, uses new ways to communicate and collaborate, can become a leader, shifts from knowledge worker to a learning worker, and learns and teaches/mentors at will. Future workers can and shall work from co-working spaces, and can be a part of a gig economy where s/he contributes to multiple organizations at the same time being paid by all, or focuses on one for a project and then on finishing it, focuses on another organization and project, without technically being employed permanently by anyone.
Such a work force will decreasingly depend on universities and long-drawn degree education. Already, Facebook, Amazon, Apple and Google have announced that they will hire from 2020 by skills and not degrees. The degree-centricity of traditional university system will lose its value. Education is becoming modular where students are taking courses they like instead of committing themselves to entire majors with a linear long drawn progression. Massive Online Open Courses (MOOC), courses of Udemy or Coursera, Udacity or Khan University are examples where learners can learn at low or no costs, and the order of tomorrow is micro certification of focused courses.

The past employees worked 9 to 5 in a corporate office, using company equipment, focused on inputs with a pre-defined work, and wanting to climb the corporate ladder. S/he hoarded information, had no voice, relied on emails, was focused on knowledge through corporate learning and teaching. But the employee of tomorrow shall work anytime, anywhere, use any device, will be focused on outputs, and create his/her own ladder. S/he will take up customized work, will share information, can become a leader, will rely on collaborative technologies, and will focused on adaptive and democratized learning.

The concept of gig or freelancer economy will also gain ground ahead. The freelancer economy is about people being able to leverage their skills and expertise to find work without having to seek full-time employment in a single company. Most of their projects are done in a virtual environment and include services like SEO, marketing and PR, content creation, web development, virtual assistants, designing, etc.

Future managers at workplaces

The ten principles of future manager according to Jacob Morgan include leadership, following from the front, understanding technology, leading by example, embracing vulnerability, believing in sharing and collective intelligence, is a fire-starter, giving real-time recognition and feedback, is conscious of personal boundaries and limitations, and adapts to the future employee.  Following from the front means that when it comes to the future of work, the goal of the managers is to remove roadblocks from the paths of employees in order to help them succeed while empowering them to work in a way that makes them engaged and effective. To be a fire-starter, managers of the future must challenge conventional ideas about management and work and not just take things in the face value, and can ditch the existing template to create a new one. 

The past manager commanded leadership, was supported by employees, relied on IT for technology, is unemotional, with a nature to control information, conforming to conventions, believing in annual reviews, and limiting himself to implicit boundaries.
The future manager earns leadership, supports the employees, understands technology, leads by example, embraces vulnerability, reaps collective intelligence, challenges convention, gives real-time feedback and recognition, and has dynamic evolving boundaries.

Future organizations to work for

On similar lines, the future organizations will also evolve or perish. Future organizations will be nationally/globally distributed with smaller teams, will have a connected work-force, will be entrepreneurial encouraging entrepreneurship skills at managerial level, will be big but operating like a small company, and will focus on want instead of need. Such a company will adapt to changes faster, will bring in innovation anywhere, will run in the cloud, will seek better gender balance in senior management, and will have a flatter structure (less hierarchy). Such companies will have stories to share, will democratize learning, shift from profit to prosperity (more holistic), and will adapt to the future employee and manager.

The Ringelmann Effect is a fascinating tendency for individual members to become less productive as the size of the group increases. Hence small units, small company approach, lean organization and entrepreneurial skills of managers will make future companies do well. Such managers will focus on what the company needs to survive and grow, and not on wants which often are wishes and embellishments.

Universities of tomorrow

Hence, going beyond degree-centricity, universities of tomorrow should consider degrees as an outcome by the way, and focus on real-life skills and literacies outlined above. It must collaborate with a myriad of learning systems, adapt to experiential brick and portal learning, focus on mentoring rather than teaching, and make education choice-based and learner centric. It must integrate formal with self-learning modules and skills. It should be focused on today and tomorrow more than yesterday, and on application of knowledge more than knowledge per se. It should create the human resources of tomorrow for economy yet not seen, rather than labour force for the economy of yesterday.

The universities of tomorrow hence prepare talent for Digital Marketers, Animators-Designers, Artificial Intelligence Engineers, Strategists, Market Researchers, Content Developers, Law Experts, Finance Experts, Multi-linguists, Behavioural Scientists, Entrepreneurs, Robotics Engineers, Communicators, Applied Scientists, Pharmacists, Design Thinkers & Designers, Big Data Analysts & Data Managers, Campaign Managers, et al. 

The approach of mentoring-learning in universities of tomorrow hence will include a blend of classroom learning (Formal), Workshop based learning (Hands-on), Peer Learning, Experiential Learning (Projects), Real Life Experiences (Internship), Case-study based Learning, Internet based Learning, Video-conferencing, International Learning (global exposure), Research based Learning, Degree & Beyond, Skill & Portfolio focus, Team-work, Problem Solving Learning.

The author is Pro Vice Chancellor of Kolkata based
Adamas University, and former Dean of Symbiosis and Amity Universities,
Pearl Academy & Whistling Woods International

Source: http://www.eindependentbd.com/home/page/2019-10-10/7

11
Research Publications / GCC Wealth Insight Report
« on: October 05, 2019, 05:42:36 PM »
Please find herewith the downloadable link of GCC Wealth Insight Report 2019

The web link: https://www.eibank.com/insight-report-2019

12
The State of Digital Investments in MENA 2013-2018 Report
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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:

Link: https://www.arabnet.me/english/business-intelligence/digital-investment-2019

13
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:

https://www.cbinsights.com/research/report/fintech-trends-2019/

14
ARTIFICIAL INTELLIGENCE (AI), MACHINE LEARNING (ML), RESPONSIBLE FINANCE (RF) – AND US, HUMANS

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.

Source: https://www.linkedin.com/pulse/artifical-intelligence-ai-machine-learning-ml-finance-kaiser-naseem/

15
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.

WHAT STUDENTS SAY ABOUT TEACHERS

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.

 A PORTRAIT OF THE STUDENT AS LAZY, CHILDISH AND UNPRINCIPLED

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.

THE UNSAVOURY ASPECTS OF THE LIVES OF UNIVERSITY STUDENTS IN DHAKA

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.

EMOTIONS, INEXPERIENCE, AND OTHER PROBLEMS OF SETS

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.”

SOLUTION

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 aliza.hridula@gmail.com


Source: https://www.thedailystar.net/shout/news/teachers-under-the-microscope-1808284

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