Learning to Lead

Source: NYTimes, Apr 2015

Is leadership an emergent quality, both situational and context-specific? Or is it something you can actually teach? That is, can you be a leader without ever leading something? Business schools insist you can.

In his 2007 history of the M.B.A., “From Higher Aims to Hired Hands,” Rakesh Khurana, dean of Harvard College and a professor of leadership development, delineated the various pedagogical approaches.

Most lie along a spectrum, with explicit knowledge and theory on one end and skill and technique on the other. Kenan-Flagler at the University of North Carolina, for example, leans heavily on sociology and psychology in constructing a “scientific” approach to the task. Kellogg, Wharton at the University of Pennsylvania and Booth at the University of Chicago, on the other hand, emphasize role-playing and team-building exercises to develop leadership experience.

A third approach involves a deep dive into one’s own values and ideals, with the ultimate goal to be an “authentic” enough leader that others will march to the tune you’re playing. According to one course description at Harvard, authentic leaders “exhibit high standards of integrity, take responsibility for their actions, and are guided by enduring principles rather than short-term experience.”

Leadership development, Dr. Khurana says, is “a personal journey.” Most schools incorporate all three approaches, addressing the tangible skills of leadership — the ability to work in teams, influence others, manage conflict and communicate.

Star Trek on the International Space Station

Source: Mashable, Apr 2015

HBS Professor Clayton Christensen’s autograph

of my copy of the Innovator’s Dilemma

Clay Christensen Autograph 001

Yuri Manin: Good Proofs are Proofs that Make Us Wiser

Source: Russian website, 1998

How do you think the 20th century will be looked at from an historical point of view? Was it an important century?

I think so. Mathematics of this century succeeded in harmonizing and unifying diverse fields on a scale probably never seen before.

Wisdom lives in connections.

What do you think is the cultural role of mathematics?

In my opinion, the basis of all human culture is language, and mathematics is a special kind of linguistic activity.

Natural language is an extremely flexible tool of communicating essentials required for survival, of expressing one’s emotions and enforcing one’s will, of creating virtual worlds of poetry and religion, of seduction and conviction.

However, natural language is not very well fit for acquiring, organizing and keeping our growing understanding of nature, which is the most characteristic trait of the modern civilization. Aristotle was arguably the last great mind that stretched this capability of language to its limits.

With the advent of Galileo, Kepler and Newton, the natural language in sciences was relegated to the role of a high level mediator between the actual scientific knowledge encoded in astronomical tables, chemical formulas, equations of quantum field theory, databases of human genome on the one hand, and our brains on the other hand.

Using the natural language in studying and teaching sciences, we bring with it our values and prejudices, poetical imagery, passion for power and trickster’s skills, but nothing really essential for the content of the scientific discourse.

Everything that is essential, is carried out either by long lists of more or less well structured data, or by mathematics.

For this reason I believe that mathematics is one of the most remarkable achievements of culture, and my life-long preoccupation with mathematics in the capacity of researcher and teacher still leaves me with awe and admiration by the end of every working day.

However, I do not believe that I can convincingly defend this conviction in the context of contemporary public debate on science and human values.

 On my private list of values a place of honor is held by the Renaissance term “varietà” — richness of life and world matched with variety of experience and thought, achieved by great minds which we try to emulate.

Yuri Manin: An Interview

Source: AMS, Nov 2009

Gelfand: You mentioned computers. What has changed in mathematics since their appearance?

Manin:  What has changed in pure mathematics?  The unique possibility of doing large-scale physical experiments in mental reality arose. We can try the most improbable things. More exactly, not the most improbable things, but things that Euler could do even without a computer. Gauss could also do them. But now, what Euler and Gauss could do, any mathematician can do, sitting at his desk.

The story of the development of the general theory of relativity is a striking example. Not only did Einstein not know the mathematics he needed, but he didn’t even know that such mathematics existed when he started understanding the general theory of relativity in 1907 in his own brilliantly intuitive language. After several years dedicated to the study of quanta, he returned to gravitation and in 1912 wrote to his friend Marcel Grossmann: “You’ve got to help me, or I will go out of my mind!”

A program arises when a great math ematical mind sees something as a whole, or not as a whole, but as something more than a single detail. But it is seen at first only vaguely.

Software Development Cost Comparison

Source: TechCrunch, Apr 2015

The best app developers in the U.S. charge $250 per hour while the best in Indonesia charge about $20 per hour. That’s 12.5x difference in how app developers price their services. Of course, there is purchase-power parity and a host of other reasons, such as time zone, language, product culture and exposure that account for some of the difference. 

A Polyarchy of Social Machines

Source: World Wide Web Conference, May 2013

The state of the art in human interaction with computational systems blurs the line between computations performed by machine logic and algorithms, and those that result from input by humans, arising from their own psychological processes and life experience. Current socio-technical systems, known as ‘social machines’ exploit the large-scale interaction of humans with machines.

In this paper we explore the landscape of social machines, both past and present,
with the aim of defining an initial classificatory framework. Through a number of knowledge elicitation and refinement exercises we have identified the polyarchical relationship between infrastructure, social machines, and large-scale social initiatives. Our initial framework describes classification constructs in the areas of contributions, participants, and motivation.

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