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👓 Algorithmic Information Dynamics: A Computational Approach to Causality and Living Systems From Networks to Cells | Complexity Explorer | Santa Fe Institute

Read Algorithmic Information Dynamics: A Computational Approach to Causality and Living Systems From Networks to Cells (Complexity Explorer | Santa Fe Institute)

About the Course:

Probability and statistics have long helped scientists make sense of data about the natural world — to find meaningful signals in the noise. But classical statistics prove a little threadbare in today’s landscape of large datasets, which are driving new insights in disciplines ranging from biology to ecology to economics. It's as true in biology, with the advent of genome sequencing, as it is in astronomy, with telescope surveys charting the entire sky.

The data have changed. Maybe it's time our data analysis tools did, too.
During this three-month online course, starting June 11th, instructors Hector Zenil and Narsis Kiani will introduce students to concepts from the exciting new field of Algorithm Information Dynamics to search for solutions to fundamental questions about causality — that is, why a particular set of circumstances lead to a particular outcome.

Algorithmic Information Dynamics (or Algorithmic Dynamics in short) is a new type of discrete calculus based on computer programming to study causation by generating mechanistic models to help find first principles of physical phenomena building up the next generation of machine learning.

The course covers key aspects from graph theory and network science, information theory, dynamical systems and algorithmic complexity. It will venture into ongoing research in fundamental science and its applications to behavioral, evolutionary and molecular biology.

Prerequisites:
Students should have basic knowledge of college-level math or physics, though optional sessions will help students with more technical concepts. Basic computer programming skills are also desirable, though not required. The course does not require students to adopt any particular programming language for the Wolfram Language will be mostly used and the instructors will share a lot of code written in this language that student will be able to use, study and exploit for their own purposes.

Course Outline:

The course will begin with a conceptual overview of the field.

Then it will review foundational theories like basic concepts of statistics and probability, notions of computability and algorithmic complexity, and brief introductions to graph theory and dynamical systems.

Finally, the course explores new measures and tools related to reprogramming artificial and biological systems. It will showcase the tools and framework in applications to systems biology, genetic networks and cognition by way of behavioral sequences.

Students will be able apply the tools to their own data and problems. The instructors will explain in detail how to do this, and will provide all the tools and code to do so.

The course runs 11 June through 03 September 2018.

Tuition is $50 required to get to the course material during the course and a certificate at the end but is is free to watch and if no fee is paid materials will not be available until the course closes. Donations are highly encouraged and appreciated in support for SFI's ComplexityExplorer to continue offering new courses.

In addition to all course materials tuition includes:

Six-month access to the Wolfram|One platform (potentially renewable by other six) worth 150 to 300 USD.

Free digital copy of the course textbook to be published by Cambridge University Press.

Several gifts will be given away to the top students finishing the course, check the FAQ page for more details.

Best final projects will be invited to expand their results and submit them to the journal Complex Systems, the first journal in the field founded by Stephen Wolfram in 1987.

About the Instructor(s):

Hector Zenil has a PhD in Computer Science from the University of Lille 1 and a PhD in Philosophy and Epistemology from the Pantheon-Sorbonne University of Paris. He co-leads the Algorithmic Dynamics Lab at the Science for Life Laboratory (SciLifeLab), Unit of Computational Medicine, Center for Molecular Medicine at the Karolinska Institute in Stockholm, Sweden. He is also the head of the Algorithmic Nature Group at LABoRES, the Paris-based lab that started the Online Algorithmic Complexity Calculator and the Human Randomness Perception and Generation Project. Previously, he was a Research Associate at the Behavioural and Evolutionary Theory Lab at the Department of Computer Science at the University of Sheffield in the UK before joining the Department of Computer Science, University of Oxford as a faculty member and senior researcher.

Narsis Kiani has a PhD in Mathematics and has been a postdoctoral researcher at Dresden University of Technology and at the University of Heidelberg in Germany. She has been a VINNOVA Marie Curie Fellow and Assistant Professor in Sweden. She co-leads the Algorithmic Dynamics Lab at the Science for Life Laboratory (SciLifeLab), Unit of Computational Medicine, Center for Molecular Medicine at the Karolinska Institute in Stockholm, Sweden. Narsis is also a member of the Algorithmic Nature Group, LABoRES.

Hector and Narsis are the leaders of the Algorithmic Dynamics Lab at the Unit of Computational Medicine at Karolinska Institute.

TA:
Alyssa Adams has a PhD in Physics from Arizona State University and studies what makes living systems different from non-living ones. She currently works at Veda Data Solutions as a data scientist and researcher in social complex systems that are represented by large datasets. She completed an internship at Microsoft Research, Cambridge, UK studying machine learning agents in Minecraft, which is an excellent arena for simple and advanced tasks related to living and social activity. Alyssa is also a member of the Algorithmic Nature Group, LABoRES.

The development of the course and material offered has been supported by:

The Foundational Questions Institute (FQXi)

Wolfram Research

John Templeton Foundation

Santa Fe Institute

Swedish Research Council (Vetenskapsrådet)

Algorithmic Nature Group, LABoRES for the Natural and Digital Sciences

Living Systems Lab, King Abdullah University of Science and Technology.

Department of Computer Science, Oxford University

Cambridge University Press

London Mathematical Society

Springer Verlag

ItBit for the Natural and Computational Sciences and, of course,

the Algorithmic Dynamics lab, Unit of Computational Medicine, SciLifeLab, Center for Molecular Medicine, The Karolinska Institute

Class Introduction:Class IntroductionHow to use Complexity Explorer:How to use Complexity Explorer

Course dates: 11 Jun 2018 9pm PDT to 03 Sep 2018 10pm PDT

Syllabus

A Computational Approach to Causality

A Brief Introduction to Graph Theory and Biological Networks

Elements of Information Theory and Computability

Randomness and Algorithmic Complexity

Dynamical Systems as Models of the World

Practice, Technical Skills and Selected Topics

Algorithmic Information Dynamics and Reprogrammability

Applications to Behavioural, Evolutionary and Molecular Biology

FAQ

Another interesting course from the SFI. Looks like an interesting way to spend the summer.

🔖 Bullshit Jobs: A Theory by David Graeber

Bookmarked Bullshit Jobs: A Theory by David Graeber (Simon & Schuster)

From bestselling writer David Graeber, a powerful argument against the rise of meaningless, unfulfilling jobs, and their consequences.

Does your job make a meaningful contribution to the world? In the spring of 2013, David Graeber asked this question in a playful, provocative essay titled “On the Phenomenon of Bullshit Jobs.” It went viral. After a million online views in seventeen different languages, people all over the world are still debating the answer.

There are millions of people—HR consultants, communication coordinators, telemarketing researchers, corporate lawyers—whose jobs are useless, and, tragically, they know it. These people are caught in bullshit jobs.

Graeber explores one of society’s most vexing and deeply felt concerns, indicting among other villains a particular strain of finance capitalism that betrays ideals shared by thinkers ranging from Keynes to Lincoln. Bullshit Jobs gives individuals, corporations, and societies permission to undergo a shift in values, placing creative and caring work at the center of our culture. This book is for everyone who wants to turn their vocation back into an avocation.

🔖 Churchill and Orwell: The Fight for Freedom by Thomas E. Ricks

Bookmarked Churchill and Orwell: The Fight for Freedom by Thomas E. Ricks (Penguin Press)

A New York Times Book Review Notable Book of 2017

A dual biography of Winston Churchill and George Orwell, who preserved democracy from the threats of authoritarianism, from the left and right alike.

Both George Orwell and Winston Churchill came close to death in the mid-1930's—Orwell shot in the neck in a trench line in the Spanish Civil War, and Churchill struck by a car in New York City. If they'd died then, history would scarcely remember them. At the time, Churchill was a politician on the outs, his loyalty to his class and party suspect. Orwell was a mildly successful novelist, to put it generously. No one would have predicted that by the end of the 20th century they would be considered two of the most important people in British history for having the vision and courage to campaign tirelessly, in words and in deeds, against the totalitarian threat from both the left and the right. In a crucial moment, they responded first by seeking the facts of the matter, seeing through the lies and obfuscations, and then they acted on their beliefs. Together, to an extent not sufficiently appreciated, they kept the West's compass set toward freedom as its due north.

It's not easy to recall now how lonely a position both men once occupied. By the late 1930's, democracy was discredited in many circles, and authoritarian rulers were everywhere in the ascent. There were some who decried the scourge of communism, but saw in Hitler and Mussolini "men we could do business with," if not in fact saviors. And there were others who saw the Nazi and fascist threat as malign, but tended to view communism as the path to salvation. Churchill and Orwell, on the other hand, had the foresight to see clearly that the issue was human freedom—that whatever its coloration, a government that denied its people basic freedoms was a totalitarian menace and had to be resisted.

In the end, Churchill and Orwell proved their age's necessary men. The glorious climax of Churchill and Orwell is the work they both did in the decade of the 1940's to triumph over freedom's enemies. And though Churchill played the larger role in the defeat of Hitler and the Axis, Orwell's reckoning with the menace of authoritarian rule in Animal Farm and 1984 would define the stakes of the Cold War for its 50-year course, and continues to give inspiration to fighters for freedom to this day. Taken together, in Thomas E. Ricks's masterful hands, their lives are a beautiful testament to the power of moral conviction, and to the courage it can take to stay true to it, through thick and thin.

🔖 Ten Arguments For Deleting Your Social Media Accounts Right Now by Jaron Lanier

Bookmarked Ten Arguments For Deleting Your Social Media Accounts Right Now by Jaron Lanier (Henry Holt and Co.)

You might have trouble imagining life without your social media accounts, but virtual reality pioneer Jaron Lanier insists that we’re better off without them. In Ten Arguments for Deleting Your Social Media Accounts Right Now, Lanier, who participates in no social media, offers powerful and personal reasons for all of us to leave these dangerous online platforms.

Lanier’s reasons for freeing ourselves from social media’s poisonous grip include its tendency to bring out the worst in us, to make politics terrifying, to trick us with illusions of popularity and success, to twist our relationship with the truth, to disconnect us from other people even as we are more “connected” than ever, to rob us of our free will with relentless targeted ads. How can we remain autonomous in a world where we are under continual surveillance and are constantly being prodded by algorithms run by some of the richest corporations in history that have no way of making money other than being paid to manipulate our behavior? How could the benefits of social media possibly outweigh the catastrophic losses to our personal dignity, happiness, and freedom? Lanier remains a tech optimist, so while demonstrating the evil that rules social media business models today, he also envisions a humanistic setting for social networking that can direct us toward a richer and fuller way of living and connecting with our world.

This looks like an interesting book to read for some related IndieWeb research. Perhaps something Greg McVerry could use in his proposed talk?

Ten Arguments for Deleting Your Social Media Accounts Right Now by Jaron Lanier

Rear cover with outline of the ten arguments

🔖 Taft Test – Web Dev Placeholder Image Generator

Bookmarked Taft Test - Web Dev Placeholder Image Generator (tafttest.com)

Does your site pass the Taft Test? Generate or swap images of Taft for web development.

I wish I had lots of bookmarklets that did quirky things like this. Interestingly this one has a relatively useful use-case in addition to its unintended comedic service.

🔖 How To Code in Python: Using Manifold to Deliver an Open Educational Resource | Building Manifold

Bookmarked How To Code in Python: Using Manifold to Deliver an Open Educational Resource (blog.manifoldapp.org)

Recently, my eBook on Python programming, How To Code in Python 3, was made available as a Manifold publication. I would like to offer my perspective to the Manifold community to give some background on the work and how I believe the Manifold platform provides additional layers of value to the text through providing a place for learning and idea exchange in both university communities and broader publics.

An interesting article about OER relating to a book that looks interesting to read.

About the Course:

Course Outline:

About the Instructor(s):

Syllabus

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