Tuesday, 30 April 2019


Let’s Know What’s There In The Book

FUNDAMENTALS OF BIOANALYTICAL TECHNIQUES AND INSTRUMENTATION, Second Edition
By Sabari Ghosal & Anupama Sharma Avasthi
This thoroughly revised edition of the book demonstrates principle and instrumentation of each technique routinely used in biotechnology. Like the previous edition, the second edition also follows non-mathematical approach. Three aspects of each technique including principle, methodology with knowledge of different parts of an instrument; and applications have now been discussed in the text. For the beginners, the book will help in building a strong foundation, starting from the preparation of solutions, extraction, separation and analysis of biomolecules to the characterisation by spectroscopic methods—the full gamut of biological analysis.

NEW TO THE SECOND EDITION
• Incorporates two new chapters on 'Radioisotope Tracer Techniques' and 'Basic Molecular Biology Techniques and Bioinformatics'.

• Comprises a full chapter on 'Fermentation and Bioreactors' Design and Instrumentation' (the revised and updated version of Miscellaneous Methods of the previous edition).

• Contains a number of pictorial illustrations, tables and worked-out examples to enhance students' understanding of the topics.

• Includes chapter-end review questions.

TARGET AUDIENCE
• B.Sc./B.Tech (Biotechnology)

• M.Sc./M.Tech (Biotechnology)


Monday, 29 April 2019


News You May Use

IIT-Bombay to start new MTech course on educational technology to create specialised workforce
There is a shortage of qualified ET experts in research labs, curriculum designing roles in schools, colleges and industries that create educational applications, reports Shivangi Mishra, Education Times, April 8, 2019

The demand for non-traditional education is growing but there is a shortage of qualified educational technology (ET) professionals and researchers. With an aim to bridge the gap, Indian Institute of Technology, Bombay (IIT-B) will introduce MTech in Educational Technology (ET) programme from the upcoming academic session.

“While the country is moving towards digital learning, there is a shortage of qualified ET experts in various research labs, curriculum design roles in schools, colleges and industries for creating educational applications, training departments for online and remote trainings, and content development industries for creation of technology-enhanced learning material and field implementation works,” says Veenita Shah, research-scientist and spokesperson, ET, IIT-B.

The primary reason for this dearth is that ET is an emerging discipline and there are not many dedicated courses at the undergraduate or postgraduate levels.

The programme will screen learners from diverse background who have keen interest in improving technology-based teaching and learning. “Educational Technology is an interdisciplinary field. The broad objective of the programme is to build specialised ET workforce with student expertise in theories of learning and pedagogy, analysis, design, effective implementation and evaluation of learning environments, instructional design, research methodologies, and translating research into practices,” says Sridhar Iyer, head of the department.

Course Structure
The two-year programme will constitute course work, emerging educational technologies, research methods and statistics, designing learning environments and adaptive learning along with on-field projects. The candidates will work on research that has been categorised into four areas, namely Technology-enhanced Learning of Thinking Skills (TELoTS), Teacher Use of Educational Technologies (TUET), Educational Data Analytics (EDA) and Emerging Technologies (EmergE).

Challenges
Apart from the lack of qualified education technology professionals to design informed solutions to existing challenges in our education system, another challenge is the effective integration of strategic pedagogy and technology.

“Efforts are being made by our department in training teachers across India as part of our focal research. More than 10,000 teachers have been trained through large-scale workshops and massive open online courses (MOOC) initiatives in research-based pedagogical strategies, technology integration and analytics,” says Shah.

For more information click http://social.phindia.com/iWfWhMSH

Sunday, 28 April 2019


Releasing Soon

ASSESSMENT FOR LEARNING By S. K. Mangal & Shubhra Mangal

The book is a rich source of information relevant to the field of assessment and learning. It describes various techniques and methods for evaluating the potential, ability, interest and attitude of learners for understanding the ways to further build up the pyramid of their learning.

It covers exhaustive information inclusive of that required for the compulsory paper “Assessment for Learning” introduced in the curriculum of B.Ed. course of various Indian universities in accordance with the guidelines of National Council for Teacher Education (NCTE).

It discusses Revised Bloom's Taxonomy of Instructional Objectives, the Construction and Standardisation of Achievement and Diagnostic Tests, Policy Perspective on Examination and Assessment, latest Assessment Tools and Devices such as Portfolio Assessment. Besides, it describes the development and use of Rubrics, Emerging Trends and Assessment Practices such as Computer-based online examination, Examination on demand, Open-book examination, and Choice-based credit system, and Statistical means and ways of analysing and interpreting students' performances.




Saturday, 27 April 2019


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Team uncovers the power of dynamically rewiring swarm robotic systems
by Singapore University of Technology and Design

Our world is filled with hopelessly complicated systems for transportation, finance, biological life, and others. These so-called complex systems, natural or man-made, are systems that are intrinsically challenging to predict due to emergent collective dynamics influenced by external environmental factors.

The complexity of these systems is rooted in the intricate interdependencies between these constitutive elements and interactions with the outside world. Understanding the propagation of exogenous perturbations is of critical importance to complex systems. For instance, think of a local shutdown at one end of the power grid, and how it can lead to a massive cascading failure, snowballing into a large-scale blackout such as the 2003 Northeast blackout in the United States. Or how a snowstorm in the New York metropolitan area triggers an avalanche of airline delays in San Francisco, Los Angeles, and throughout the West Coast. Or fads introduced by celebrities that sometimes go viral, propagate and amplify through tweets/retweets, sharing and likes.

For decentralized networked systems operating in dynamic environments, the ability to respond to changing circumstances is paramount. It can be a matter of life and death for birds flocking and maneuvering to escape a predator attack. It can also be a matter of optimal efficiency for multi-robot systems operating collectively and subjected to changing conditions. It is therefore critical to investigate and understand the influence of the network topology on the system's collective response.

With this in mind, Bouffanais and his team at the Singapore University of Technology and Design (SUTD) considered an archetypal model of distributed decision-making. The objective was to study the collective capacity of the system in responding to local external perturbations. Their theoretical network science results were verified with experiments on the collective behavior of a swarm of land robots. They revealed a nontrivial relationship between the dynamics of the perturbation and the optimal network topology. The emergent collective response of the swarm to a slow-changing perturbation increases with the degree of the interaction network, but the opposite is true for the response to a fast-changing one. Their study uncovered the existence of a specific number of interactions among units required to produce an optimal collective response.

The principal investigator, SUTD Associate Professor Roland Bouffanais, said: "Given the explosion in the development of distributed/decentralized systems, this research shows that a dynamic rewiring of the interaction network is essential to the effective collective operations of these complex engineered systems at different time scales."

To see videos of the below experiments click http://social.phindia.com/5OBfqSOa
1. Experiment to measure the collective response in leader-follower heading consensus of a swarm of N + 1 = 11 land robots with a low-frequency input signal. Credit: SUTD

2. Experiment to measure the collective response in leader-follower heading consensus of a swarm of N + 1 = 11 land robots with a high-frequency input signal. Credit: SUTD

Details of this work appeared in the Science Advances on 3 April 2019.

Source Credit: PHY.org

Friday, 26 April 2019


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How to Stop Obsessing Over Your Mistakes
By Alice Boyes, PhD is a former clinical psychologist turned writer and is author of The Healthy Mind Toolkit and The Anxiety Toolkit.

Do you ever find yourself endlessly mentally replaying situations in which you wish you’d performed differently? You wish you hadn’t said that dumb thing. You wish you’d volunteered for that project that’s now winning accolades. You wish you’d spoken up. You wish you hadn’t dropped the ball with that potential client. Overthinking in this way is called rumination. While we worry about what might occur in the future, we ruminate about events that have already happened. A ruminative reaction to an event often triggers memories of similar situations from the past and an unproductive focus on the gap between the real and ideal self. Prompted by this one event, you begin to chastise yourself for not being more of something…organized, ambitious, smart, disciplined, or charismatic.

Rumination isn’t just unpleasant. It’s closely linked to poor problem-solving, anxiety, and depression. The good news is that there are effective solutions for breaking yourself out of this rut, and they’re simpler than you might think.

Identify your most common triggers. You can’t quell rumination without noticing that you’re doing it, but people aren’t always able to spot it in themselves. A great way to get better at this is to think about what has triggered you in the past. Your list might look something like:
  Collaborating with people I don’t yet trust
  Being around people who seem smarter or more ambitious
  Taking a step up in my career
   Making major money decisions

Notice if the dominant pattern of your rumination is blaming yourself or blaming others. Most heavy ruminators lean towards one or the other of these.

Get psychological distance. Next, you need to put some psychological distance between you and the things you ruminate about. For instance, you might feel concerned about how you’re perceived by people who have no impact on your success, get hung up about very small amounts of money, or see yourself as an underachiever despite the fact that objectively you’re doing very well. One way to start to get this distance is by labeling what’s running through your head as thoughts and feelings, a tactic described in this article on emotional agility. So instead of saying “I’m inadequate,” you might say, “I’m feeling like I’m inadequate.” You can even be more light-hearted about it: “Oh, that’s just my ruminating mind overheating again.”

Recognizing the absurdity in some of your reactions can also help you take them less seriously. Look for any subtle entitlement or self-absorption hidden in your ruminations. Do you expect things to always go your way? Do you tend to believe people are scrutinizing you when, in reality, they’re probably thinking about themselves? Do you spend time comparing yourself to business superstars or celebrities? Entitlement and personalizing can indicate that you tend to think the world revolves around you. If applicable, try to see the irony in being both narcissistic and insecure, rather than viewing it as an indictment on your character. You can even try imagining an ultra-neurotic TV character version of yourself. Not every rumination topic is appropriate for this strategy but catch any that are.

Distinguish between ruminating and problem solving. Occasionally you might have a useful insight while ruminating, but mostly it’s avoidance coping. Generally, the more people ruminate, the less effective they are at problem solving. Either they don’t think of solutions or don’t pursue them quickly or effectively. For instance, one study showed that women who were heavy ruminators took over a month longer to seek medical care after finding a breast lump. To shift from rumination to improvement mode, ask yourself, “What’s the best choice right now, given the reality of the situation?” Start by taking one step, even if it’s not the most perfect or comprehensive thing you could do. This strategy is particularly relevant for perfectionists. If you’re ruminating about a mistake you’ve made, adopt a strategy that will lessen the likelihood of it happening again.

Train your brain to become non-stick. As soon as you notice you’re ruminating, try to distract yourself for a few minutes. Engage in an activity that’s short and mentally absorbing but not extraordinarily difficult, like spending 10 minutes filling out an expense report. The activity you pick should be one that requires you to concentrate. In some situations, you might be able to just refocus your attention on what you’re supposed to be doing. You might think: “How could something so simple help with my complex, emotional problem?” But this technique can be surprisingly effective.

Physical activity, such as jogging or walking, can also calm a mind that’s prone to rumination. Meditation or yoga can be especially helpful for protecting yourself from sticky thoughts and learning not to over-engage with them. These practices ask you to notice when your mind has wandered off to the past or future and bring it back to what’s happening in the present (often your breathing or other sensations in your body or surroundings.)  This is exactly the skill you need for coping with moments of rumination.

Check your thinking for errors. Sometimes rumination is triggered by cognitive errors. The catch-22 is that you’re not likely to be very good at detecting distorted thinking when you’re ruminating, since it clouds thinking. The solution is to develop a good understanding of your typical thinking errors, over time, in calm moments so that you’re still able to recognize them when you’re feeling heightened emotions. Here’s a personal example: I’ll often read a work-related email and zone in on one or two sentences that irritate or upset me and then misinterpret the overall tone of the message as demanding or dismissive. But, because I’m aware of this pattern, I’ve learned to not ruminate over my initial impressions. Instead, I read the email again after a day’s cool down, and usually see that I had a biased impression of it.

Other common cognitive errors include setting too-high self-expectations, misinterpreting others’ expectations of you, underestimating the extent to which other smart people struggle with what’s troubling you, and making mountains out of molehills. If you’re ruminating about someone else’s behavior and attributing a cause to that behavior, at least entertain the idea that your explanation is wrong and try to accept that you might never know the truth. Recognizing that we often won’t understand the reasons for someone else’s behavior is a hugely important skill in reducing rumination.

Rumination is a widespread problem. Before you can break out of it, you need to become more aware of when you’re doing it and have resistance strategies ready to go. This takes time and effort. But it’s important — for your mental health and productivity — to try to nip it in the bud. So, before you go deep into your next “would have, should have, could have” spiral, give one or more of these ideas a go.

Source Credit: Harvard Business Review
Click here to read in full http://social.phindia.com/4DDn7wAP






Thursday, 25 April 2019


Business Communication Series

Importance of Business Letter
Letter is as an indispensable tool of communication in business. Business letters are used to sell the products, make inquiry about customers or prices of goods, seek information and advice, maintain good public relation, increase goodwill and perform a variety of other business functions. With the continuous growth of commerce and industry, usefulness and importance of business letter are also increasing gradually. Some points highlighting the benefits or importance of business letter are discussed below:

  • Exchanging business information: Letters are the most economic and convenient means of exchanging information. With the help of letters, executives can easily exchange information with customers, suppliers, investors, government offices; regulatory authorities etc.

  • Establishing business relationship: Business letter play important role in establishing and maintaining relationship with various parties. Business letters reduce the distance between a business and its customers, suppliers, creditors and other public groups.

  • Creation of markets: Circular letter a form of business letter, helps to create new markets for goods and services. This letter contains information about utility, features and usefulness of the products and induces the customer to buy the products.

  • Substitute to personal visit: Introduction of letters in business world relieves the business executives’ form visiting their clients, suppliers, creditors and other public groups by traveling a long distance. For this reason, commercial letters are called alternative technique to personal visit.

  • Saving cost and time: Business letters relieve the busy executives from visiting personally their clients and other concerned parties. Therefore, valuable time and costs can be saved.


  • Maintaining secrecy: Business letters also help to maintain secrecy of information. Non one other than the sender and receiver can know the message contained in the letter.

  • Increasing goodwill: Business letters, like inquiry letter, circular letter, order acknowledgement letter, adjustment grant letter etc help to increase good will of a business with the customers.

  • Formal agreement: Business letter acts as formal agreement between buyer and seller. For example an order letter contains name of items, price, and quantity, time of delivery and mode of payment. All these are regarded as the conditions of agreement between buyer and seller.

  • Settlement of transaction: Commercial letters have paramount importance in setting business transaction. For example, by writing claim letter, buyer can raise his claims to the seller by writing collection letters; seller can collect dues from the customers.

  • Use as reference: Information exchanged through letters can be preserved permanently and used as reference when need arise. Therefore, making business decisions becomes easier.

  • Legal acceptance: Business letter is an acceptable document in the eye of law. It can be stored and produced as a documentary proof.

  • Assistance in local and international trade: Both local and foreign trade essentially requires the help of various business letters. Through letters, businessperson make inquiry about products and prices place orders for goods collect the dues make and settle claims etc.

From the above discussion, it can be concluded that successful operation of business activities establishing, maintaining and developing business relationship and finally achieving business goal all require help of business letters. In a sense, conducting business is impossible without business letters.

Source Credit: The Business Communication


Tuesday, 23 April 2019

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World Book and Copyright Day

World Book and Copyright Day is a celebration to promote the enjoyment of books and reading. Each year, on 23 April, celebrations take place all over the world to recognize the scope of books - a link between the past and the future, a bridge between generations and across cultures. On this occasion, UNESCO and the international organizations representing the three major sectors of the book industry - publishers, booksellers and libraries, select the World Book Capital for a year to maintain, through its own initiatives, the impetus of the Day’s celebrations. 

23 April is a symbolic date in world literature. It is the date on which several prominent authors, William Shakespeare, Miguel Cervantes and Inca Garcilaso de la Vega all died. This date was a natural choice for UNESCO's General Conference, held in Paris in 1995, to pay a world-wide tribute to books and authors on this date, encouraging everyone to access books.

By championing books and copyright, UNESCO stands up for creativity, diversity and equal access to knowledge, with the work across the board – from the Creative Cities of Literature network to promoting literacy and mobile learning and advancing Open Access to scientific knowledge and educational resources. With the active involvement of all stakeholders: authors, publishers, teachers, librarians, public and private institutions, humanitarian NGOs and the mass media, and all those who feel motivated to work together in this world celebration of books and authors, World Book and Copyright Day has become a platform to rally together millions of people all around the world.

To know more click https://en.unesco.org/commemorations/worldbookday
Celebrate World Book and
Copyright Day Today!


Monday, 22 April 2019


What is Earth Day, and what is it meant to accomplish?

A message from President, Kathleen Rogers:

On April 22, 1970, millions of people took to the streets to protest the negative impacts of 150 years of industrial development.

In the U.S. and around the world, smog was becoming deadly and evidence was growing that pollution led to developmental delays in children. Biodiversity was in decline as a result of the heavy use of pesticides and other pollutants.

The global ecological awareness was growing, and the US Congress and President Nixon responded quickly. In July of the same year, they created the Environmental Protection Agency, and robust environmental laws such as the Clean Water Act and the Endangered Species Act, among many.

One billion people
Earth Day is now a global event each year, and we believe that more than 1 billion people in 192 countries now take part in what is the largest civic-focused day of action in the world.

It is a day of political action and civic participation. People march, sign petitions, meet with their elected officials, plant trees, clean up their towns and roads. Corporations and governments use it to make pledges and announce sustainability measures. Faith leaders, including Pope Francis, connect Earth Day with protecting God’s greatest creations, humans, biodiversity and the planet that we all live on.

Earth Day Network, the organization that leads Earth Day worldwide, has chosen as the theme for 2018 to End Plastic Pollution, including creating support for a global effort to eliminate primarily single-use plastics along with global regulation for the disposal of plastics.  EDN is educating millions of people about the health and other risks associated with the use and disposal of plastics, including pollution of our oceans, water, and wildlife, and about the growing body of evidence that plastic waste is creating serious global problems.

From poisoning and injuring marine life to the ubiquitous presence of plastics in our food to disrupting human hormones and causing major life-threatening diseases and early puberty, the exponential growth of plastics is threatening our planet’s survival.

Earth Day 2020: 50th Anniversary of Earth Day!
Get the scoop on Earth Day Network’s big plans for 2020, the 50th anniversary of Earth Day: citizen science, clean-ups and tree-planting, huge events, and more.

Earth Day 2019: Protect Our Species

Earth Day 2018 and Beyond: End Plastic Pollution
EDN built a multi-year campaign to End Plastic Pollution. Our goals include ending single-use plastics, promoting alternatives to fossil fuel-based materials, promoting 100 percent recycling of plastics, corporate and government accountability and changing human behavior concerning plastics. EDN’s End Plastic Pollution campaign includes four major components:
  • Leading a grassroots movement to support the adoption of a global framework to regulate plastic pollution;
  • Educating, mobilizing and activating citizens across the globe to demand that governments and corporations control and clean up plastic pollution;
  • Educating people worldwide to take personal responsibility for plastic pollution by choosing to reduce, refuse, reuse, recycle and remove plastics and
  • Promoting local government regulatory and other efforts to tackle plastic pollution.


Today on Earth Day let’s get to know about Ecology with ESSENTIALS OF ECOLOGY AND ENVIRONMENTAL SCIENCE, Second Edition By Rana; dive into Biodiversity with BIODIVERSITY : PERCEPTION, PERIL AND PRESERVATION, Second Edition By Mait & Maiti; And acquaint ourselves with WILDLIFE BIOLOGY : AN INDIAN PERSPECTIVE by Saha & Mazumdar



Sunday, 21 April 2019


Kandhal Lecture 2 - Grading of Bitumen and Polymer Modified Bitumen

This is a one-hour tutorial by Prof. Prithvi Singh Kandhal on Grading of Bitumen and Polymer Modified Bitumen. It covers penetration grading; viscosity grading; and Superpave performance grading. It also describes different types of polymer modified bitumen (PMB) and their uses. Crumb Rubber Modified Bitumen (CRMB) has also been discussed.

Slides handouts for this lecture can be accessed, downloaded, and printed at the following link to have better comprehension of the lecture and also for permanent record: https://bit.ly/2HNxOzy

This is one of 12 lectures given by Prof. Kandhal for Larson and Toubro (L&T) engineers in May 2016. These lectures were recorded by L&T who has allowed their uploading on YouTube for the benefit of highway engineers in India and across the world. Editing has been done by Prof. Kandhal who is Associate Director Emeritus, National Center for Asphalt Technology (NCAT), Auburn University, USA. His homepage is: www.eng.auburn.edu/users/kandhps

Prof. Prithvi Singh Kandhal is the co-author of the first ever textbook on asphalt technology published in the US. It is used in over 25 universities there. He has now authored the first ever textbook cum reference book in India, “Bituminous Road Construction in India” in July 2016. It has been published by PHI Learning Private Limited and is priced Rs. 525 only. To purchase, contact PHI at: customerservice@phindia.com or order on PHI Learning website. Click here https://bit.ly/2WElAwx.

Viewers should refer this textbook for getting more detailed technical information on the topic presented in this lecture or tutorial.



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What Every Entrepreneur Should Learn from these Famous Logos

Coming up with the best possible logo is very important. Many companies have struggled to find a logo that communicates the essence of their brand. If you are looking for inspiration, you need to look at some of the companies that did it right. Of course, you don’t want to outright copy of their design approach. However, you can get a sense of the approach that they took and why it worked so well.

Here are some famous logos and the lessons that you can learn from them. You shouldn’t have any trouble replicating one of these logos when you need one for your own brand. There are plenty of great logo design tools that can help you out. You may use the one suitable to your requirements. 

Target

Target has a very simple logo. It is basically just a bull’s eye made from two red rings and a white one conjoining them. This is a simplified version of its original logo, which had three bands of each color.
This logo clearly communicates its message for two reasons:
  • The logo is an obvious image that conveys the theme of the brand. The company’s name is Target and the logo is it target itself. It couldn’t be clearer.
  • Target uses very few design elements in its logo. New entrepreneurs and graphic designers might think that this is a drawback. However, this is actually one of the reasons it is so effective. People don’t want to try to make sense of overly complicated designs. Simplicity is usually best.

Target’s logo has gone unchanged for nearly 15 years, because it works so well. Their own research shows that most customers recognize it at a casual glance.
“Target’s telltale logo was first revealed in 1962, streamlined in 1968 and has since evolved into one of the most recognized symbols in North America. No, seriously — a 2003 Target study found more than 96 percent of American shoppers know what that bold, red Bullseye represents.”

Apple Computer

Apple Computer’s logo has evolved significantly over the past 43 years. It has evolved in a way that you wouldn’t expect. Instead of becoming more complex, it has actually evolved into simplicity. The 1976 version of the logo was a very complicated drawing of Isaac Newton. One year later, it was a vector-based design of an apple with six different colors. Today, the logo is still an apple with the same contours that the company has used for nearly half a century. However, the logo is completely black. It no longer uses a mixture of different hues and vectors.

Apple realize that its logo was a lot more memorable if people could recognize it at a glance. This worked a lot better using a simpler logo, which is why the Isaac Newton cartoon gave way to a basic picture of an everyday apple.

Google

Google is one of the newer companies on the New York Stock Exchange. However, its logo is already one of the most famous in the world. The company has the most popular website on the planet, so a couple billion people see it every single day. Due to its high visibility, Google couldn’t afford to get its logo wrong.

Google is another company that has thrive by using a slick, simple design. Its logo is basically a text version of its name. It has multiple colors. There is one subtle difference that people wouldn’t pick up on at first glance. One of the letters is green. It is the only letter that does not have a primary color. This is meant to signify simple differences that make the company unique. Nonetheless, the overall design is very easy to understand, even if the metaphor is lost on most people.

Use the KISS Principle for Logo Design

Designing a good logo doesn’t need to be hard. You just need to find the simplest approach possible.

Thursday, 18 April 2019


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How to Set Up an AI Center of Excellence
By Thomas H. Davenport and Shivaji Dasgupta

Artificial intelligence is one of the most powerful technologies for reshaping business in decades. It has the ability to optimize many processes throughout organizations and is already the engine behind some of the world’s most valuable platform businesses. In our view AI will become a permanent aspect of the business landscape and AI capabilities need to be sustainable over time in order to develop and support potential new business models and capabilities.

Specifically, we believe that companies need to establish dedicated organizational units to entrench AI. This is an important business tool that cannot be left to bottom-up whimsy. Companies are devoting considerable financial resources to AI, and necessary skills and experience are too rare to assume that they will be scattered around the organization with little coordination or collaboration. Just as e-commerce led to Chief Digital Officers and groups to support online presence and commerce, we believe that AI will engender new competence centers (CC) or centers of excellence (COE), and new roles within them.

The idea of establishing a CC or COE in AI is not particularly radical. In one recent survey of U.S. executives from large firms using AI, 37% said they had already established such an organization. Deutsche Bank, J.P. Morgan Chase, Pfizer, Procter & Gamble, Anthem, and Farmers Insurance are among the non-tech firms that have created centralized AI oversight groups.

Certain AI technologies are well known within many organizations. Machine learning derives its roots from statistical regression. This raises the issue of whether an AI CC or COE should be combined with analytics groups. If an existing analytics group is already doing some predictive analytics work, analysts who are willing to learn and grow can probably master many AI projects, and a combined organization would make sense.

What an AI Team Should Do
Whether an AI team is an outgrowth of an existing analytics team or an entirely new group, there are many different activities that it can and should pursue. Some of these — like developing AI models and systems, working closely with vendors, and building a technical infrastructure — can be done in collaboration with an IT organization; others will involve working closely with business leaders. Although collaboration is important, these are the tasks that the AI team should be responsible for:

Create a vision for AI in the company. It’s important for executives to discuss — ideally with AI experts — what AI is, what it can do, and how it might enable new business models and strategies. Otherwise it may sub-optimize what AI can do for the business.

Identify business-driven use-cases. Developers of AI capabilities will need a prioritized list of applications or use cases within the company. They should balance strategic value with what is achievable. Companies may develop some of these use cases as pilots or prototypes, but they should also have a “pipeline” — regularly monitored by the AI center and by executives — that leads to production deployment.

Determine the appropriate level of ambition. Since AI typically supports tasks rather than entire jobs or business processes, it is usually best to undertake less ambitious projects as opposed to “moon shots.” But in order to get management attention and have a substantial impact on the business, organizations may want to undertake a series of smaller projects in one area of the business. This may require a “road map” with multiple use cases across a timeline. An AI center can help a company “think big, but start small” with AI.

Create a target data architecture. The vision and use-cases define the data platform and tools needed to deliver. This is key for all (data-relevant) projects, to includes all types of data — structured, unstructured, and external. Hadoop is the standard data management platform today, but the AI center needs to decide between on-premises versus cloud variations, and self-maintained open source solutions versus licensed solutions (e.g. Hadoop on Cloudera or AWS or open-source). Most companies will benefit from using user-ready analytics tools with open-source components (e.g. Alteryx) to allow quick user-friendly modeling, rather than packaged tools that are historically BI-oriented (like early versions of SAS or SPSS).

Manage external innovation. An AI center can help to orchestrate relationships with universities, vendors, AI start-ups, and other sources of expertise and innovation. The company can develop an AI ecosystem, and perhaps even invest in firms that show promise of adding value to the business. This is also important for the tools and technology to be best-in-class.

Develop and maintain a network of AI champions. An AI center will work best if it cultivates a network of influential supporters and champions for the technology across the business. This step is far along in many companies; in the 2018 Deloitte survey, 45% of companies had appointed senior executives across the company as AI champions. Given the commodification of programming (with readily available scripts in languages like R- and Python), the focus for in-house capability building should be on statistical and mathematical modeling, rather than pure programming.

Spread success stories. A key success factor with AI or any new technology is to spread early success stories with prioritized use cases. This will build the appetite for more AI activity; in effect such communications perform a marketing function for the AI center.

Acquiring and Building Talent
One of the most critical factors in successfully building an AI center is recruiting, attracting, or building talent. It is no secret that leading-edge AI engineers and data scientists (statisticians) are difficult to hire—even in Silicon Valley. Most organizations will require a few people with the ability to develop and implement AI algorithms—say, a Ph.D. in AI or computer science. But many of the business-focused tasks of a center can be carried out by MBA-level analysts who have made themselves conversant with AI capabilities and who can use automated machine learning tools. It is also possible to get a faster start with AI talent by hiring consultants or vendors to work on early projects. It will be mandatory to combine them with internal employees on teams.

Companies may also want to start now in building AI talent. There is no reason why quantitatively-oriented employees can’t be trained in AI. Some companies, including Cisco Systems, worked with universities to develop data science training programs for internal employees that created hundreds of certified specialists. The same approach could be taken for AI (with some of the same content).

Also, companies like Reply and DataRobot and universities like MIT are offering short executive education courses to ensure “quick” ramp-up on AI related skills, tailor made for each company.

Organizational Structures and Processes
While there is no single best organizational structure for an AI center, we think that in most cases organizations would be well-served by a central structure with deployed or embedded staff, reporting to an enterprise-wide business function. Since AI talent is scarce, it is difficult to develop critical mass if it is scattered around the organization. And our experience with analytics functions was that centralization contributes to greater job satisfaction and retention for this type of role.

To avoid excessive bureaucracy, a centralized group should embed or assign its staff — at least some of them — to business units or functions where AI is expected to be common. That way the center staff can become familiar with the unit’s business issues and problems, and develop relationships with key executives. Rotational programs across business units can improve knowledge growth and transfer. As AI starts to become pervasive, these embedded staff may move their primary organizational reporting line to business units or functions.

There are a variety of possible areas into which an AI center might report, but we’d argue that the best one is a central strategy group that is also responsible for digital tasks. ProSiebenSat.1 (the largest private media company in Germany) positioned the data analytics team between digital business and IT to allow for a stronger focus on developing new business models for the platform economy. The AI and Analytics teams at Versicherungskammer (the largest public insurer in Germany) report to the Chief Information Officer. Procter & Gamble’s AI group was a joint effort of IT and R&D. At Anthem, the Cognitive (AI) Center of Excellence reports to the Chief Digital Officer.

As with many technologies today, AI projects are best conducted in an “agile” fashion, with many short-term deliverables and frequent meetings with stakeholders. If there needs to be substantial system development or integration, more traditional project management approaches may come into play.

Finally, given some of the ethical issues that can arise from AI, it’s important not to ignore that set of issues within an AI center. Companies may want to establish ethics-related positions or review boards as a part of their AI efforts. Microsoft, for example, has created an “AI Ethicist” role to guide businesses on such issues as algorithmic bias and the impact on consumers of AI applications.

All business resources require focus and alignment to succeed. The scarcity of AI talent and expertise means that it is even more critical than with other resource types to create critical mass for AI within a corporate center of competence or excellence. We believe it is virtually impossible to succeed as an “AI first” organization without a center devoted to the effective application of that technology.


Source Credit: Harvard Business Review
Authors:
Thomas H. Davenport is the President’s Distinguished Professor in Management and Information Technology at Babson College, a research fellow at the MIT Initiative on the Digital Economy, and a senior adviser at Deloitte Analytics. He is the author of over a dozen management books, most recently Only Humans Need Apply: Winners and Losers in the Age of Smart Machines and The AI Advantage.

Shivaji Dasgupta is a Managing Director and Head of Data Architecture and Smart Analytics for Deutsche Bank’s Private and Commercial Bank. Deutsche Bank is a founding member of the MIT Initiative on the Digital Economy (“MIT IDE”).


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