The most audacious commitment from Microsoft is its push to take carbon out of the atmosphere. The company is putting its faith in nascent technology, and it’s injecting a significant investment into a still controversial climate solution. Proponents of carbon capture, like Friedmann, say that the technology is mature enough to accomplish Microsoft’s aims. It’s just way too expensive right now. Microsoft’s backing — and its $1 billion infusion of cash — could ultimately make the tech cheaper and more appealing to other companies looking for new ways to go green.
Fantastic news. Carbon capture is a key opportunity for decelerating climate change. Hopefully more companies follow suit.
Dr. Ngumbi and Dr. Lovett outline the issues with modern research conferences that are stuck in the 20th (or even 19th) century.
By the end of each conference, you’ve heard dozens of people dispense all their knowledge in 10-minute bursts, and you sometimes leave feeling less informed than before you arrived. Where’s the dialog? Where’s the questioning? Where’s the innovation? It’s beyond time that scientific conferences themselves undergo the scientific process, and move forward.
I shouldn’t ever be surprised by these events, but every time I go to one, I am shocked by how boring the facilitation is. Some might defend the format. After all, sage-on-a-stage has worked for hundreds of years.
The question isn’t whether it works, though. It’s whether it could be better. Surely, in an age of cloud technologies and the Internet and social media—not to mention better recognition of soft power and inclusivity and the processes of scientific revolution—there are modes of conference programming that can leapfrog the conventional format.
Having led a number of events over the years that have shirked tradition for more interesting facilitation formats, I know firsthand how disruptive facilitation mistakes can be. But I’ve also seen some incredible results from shaking up the structure. Radhoc’s Unpanel, for instance, turns the structure of a panel upside-down. Instead of having a group of “experts” on a stage speaking to an anonymous crowd, the format puts those invited guests in subgroups that get to introduce one another. The audience becomes the panel, and the expert an anchor in the conversation. It gives everyone a chance to connect with the quasi-celebrities anointed by these events. As a bonus, it’s easier for the guests, too—they don’t need to prepare keynotes, only business cards.
I have a foreboding of an America in my children’s or grandchildren’s time—when the United States is a service and information economy; when nearly all the manufacturing industries have slipped away to other countries; when awesome technological powers are in the hands of a very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness…
Carl Sagan, as quoted by @Andromeda321 in this interesting Reddit thread on the regretful trends of the 2010s.
The thread discusses the growth of anti-intellectualism and conspiracy theories. I’m reminded of this timeless Medium post about how hating Ross in Friends became a meme in and of itself, reinforcing the persecution of science in the ’90s. From David Hopkins:
I want to discuss a popular TV show my wife and I have been binge-watching on Netflix. It’s the story of a family man, a man of science, a genius who fell in with the wrong crowd. He slowly descends into madness and desperation, led by his own egotism. With one mishap after another, he becomes a monster. I’m talking, of course, about Friends and its tragic hero, Ross Geller.
If you remember the 1990s and early 2000s, and you lived near a television set, then you remember Friends. Friends was the Thursday night primetime, “must-see-TV” event that featured the most likable ensemble ever assembled by a casting agent: all young, all middle class, all white, all straight, all attractive (but approachable), all morally and politically bland, and all equipped with easily digestible personas. Joey is the goofball. Chandler is the sarcastic one. Monica is obsessive-compulsive. Phoebe is the hippie. Rachel, hell, I don’t know, Rachel likes to shop. Then there was Ross. Ross was the intellectual and the romantic.
Eventually, the Friends audience — roughly 52.5 million people — turned on Ross. But the characters of the show were pitted against him from the beginning (consider episode 1, when Joey says of Ross: “This guy says hello, I wanna kill myself.”) In fact, any time Ross would say anything — about his interests, his studies, his ideas — whenever he was mid-sentence, one of his “friends” was sure to groan and say how boring Ross was, how stupid it is to be smart, and that nobody cares. Cue the laughter of the live studio audience. This gag went on, pretty much every episode, for 10 seasons. Can you blame Ross for going crazy?
People in the Reddit thread point out that these seemingly recent trends have been taking root for a long time. While this is true, it’s also true that (just like seemingly everything else) these phenomena have been moving much faster and growing much larger in recent years. Which leads to a curious tangent: how do accelerated scales of change play on our biases? Does the interaction between these biases and our accelerated experiences change our perception of the world?
Spanning all five schools at MIT, IDSS embraces the collision and synthesis of ideas and methods from analytical disciplines including statistics, data science, information theory and inference, systems and control theory, optimization, economics, human and social behavior, and network science.
The mission of IDSS is to advance education and research in state-of-the-art analytical methods and to apply these methods to address complex societal challenges in a diverse set of areas such as finance, energy systems, urbanization, social networks, and health.
IDSS comprises a number of academic programs, including those offered by the Statistics and Data Science Center (SDSC), two online education programs, and the IDSS research entities Laboratory for Information and Decision Systems (LIDS) and Sociotechnical Systems Research Center (SSRC).- https://www.prweb.com/releases/noted_mit_scientist_muncher_dahleh_joins_the_enterworks_executive_advisory_board_to_help_guide_company_s_vision_for_artificial_intelligence/prweb15872695.htm
the research process is somewhat similar, from what I have experienced. The three main steps in the data science process are:
data sourcing—more than mere access, it’s also about understanding lineage and assessing quality and coverage;
data transformation—from filtering and simple arithmetic transformations to complex abductions like predictions and unsupervised clustering; and
results delivery—both socially and programmatically (i.e., as lines of code).
Loren Grush writing for The Verge on the potential impact of the Laser Interferometer Gravitational-Wave Observatory (LIGO)’s gravitational wave discovery on research and innovation in science.
It’s the simple things in writing.
The data mindset is good for some questions, but completely inadequate for others. But try arguing that with someone who insists on seeing the numbers.
The promise is that enough data will give you insight. Retain data indefinitely, maybe waterboard it a little, and it will spill all its secrets.
There’s a little bit of a con going on here. On the data side, they tell you to collect all the data you can, because they have magic algorithms to help you make sense of it.
On the algorithms side, where I live, they tell us not to worry too much about our models, because they have magical data. We can train on it without caring how the process works.
The data collectors put their faith in the algorithms, and the programmers put their faith in the data.
At no point in this process is there any understanding, or wisdom. There’s not even domain knowledge. Data science is the universal answer, no matter the question.— From Maciej Cegłowski’s talk at the Strata+Hadoop 2015 conference in NYC.
Kepler’s astronomers decided to found Planet Hunters, a program that asked “citizen scientists” to examine light patterns emitted by the stars, from the comfort of their own homes.
In 2011, several citizen scientists flagged one particular star as “interesting” and “bizarre.” The star was emitting a light pattern that looked stranger than any of the others Kepler was watching.— Citizen scientists provide the backbone for the latest viral astronomical headline.
Get a rat and put it in a cage and give it two water bottles. One is just water, and one is water laced with either heroin or cocaine. If you do that, the rat will almost always prefer the drugged water and almost always kill itself very quickly, right, within a couple of weeks. So there you go. It’s our theory of addiction.
Bruce comes along in the ’70s and said, “Well, hang on a minute. We’re putting the rat in an empty cage. It’s got nothing to do. Let’s try this a little bit differently.” So Bruce built Rat Park, and Rat Park is like heaven for rats. Everything your rat about town could want, it’s got in Rat Park. It’s got lovely food. It’s got sex. It’s got loads of other rats to be friends with. It’s got loads of colored balls. Everything your rat could want. And they’ve got both the water bottles. They’ve got the drugged water and the normal water. But here’s the fascinating thing. In Rat Park, they don’t like the drugged water. They hardly use any of it. None of them ever overdose. None of them ever use in a way that looks like compulsion or addiction. There’s a really interesting human example I’ll tell you about in a minute, but what Bruce says is that shows that both the right-wing and left-wing theories of addiction are wrong. So the right-wing theory is it’s a moral failing, you’re a hedonist, you party too hard. The left-wing theory is it takes you over, your brain is hijacked. Bruce says it’s not your morality, it’s not your brain; it’s your cage. Addiction is largely an adaptation to your environment.
We’ve created a society where significant numbers of our fellow citizens cannot bear to be present in their lives without being drugged, right? We’ve created a hyperconsumerist, hyperindividualist, isolated world that is, for a lot of people, much more like that first cage than it is like the bonded, connected cages that we need.
The opposite of addiction is not sobriety. The opposite of addiction is connection. And our whole society, the engine of our society, is geared towards making us connect with things. If you are not a good consumer capitalist citizen, if you’re spending your time bonding with the people around you and not buying stuff—in fact, we are trained from a very young age to focus our hopes and our dreams and our ambitions on things we can buy and consume. And drug addiction is really a subset of that.—
Hm. A brief skim of some of the research done on Bruce Alexander’s “Rat Park” in the last few decades and the Wikipedia article on the subject seems to indicate that the conclusion drawn here isn’t as straightforward as we’d like, but overall, it looks like this subject should be studied more. Disappointing that the SFU studies ran out of funding.
Still, it’s an interesting thought, and an important contrast to prevailing views on addiction (as Johann Hari suggests).
). In hindsight, this seems obvious to me. If the aging process is biological (which it obviously is) then there has to be differences in how it happens in people. Still, the implications are huge. I’m reminded of Google’s anti-aging startup, Calico. Maybe Calico can develop treatments for the people that age “quickly” as an early type of aging intervention… Hm.
Ageing rates vary widely, says study http://t.co/qoiVutPlk0— BBC News (World) (@BBCWorld) July 7, 2015