Having students create and work with robots offers them a range of skills, she said, noting that the district once participated in a regional tournament through NASA at the Jet Propulsion Laboratory in Pasadena but that the program ended a few years ago.
“I think it really teaches them to think critically,” she said. “It gives them programming and computer science skills, as well as engineering skills, because they have to think of the task involved and design the robot to complete that task. A huge element of it is collaboration and how well they can work together.”
High-profile physicists and philosophers gathered to debate whether we are real or virtual—and what it means either way.
If you, me and every person and thing in the cosmos were actually characters in some giant computer game, we would not necessarily know it. The idea that the universe is a simulation sounds more like the plot of “The Matrix,” but it is also a legitimate scientific hypothesis. Researchers pondered the controversial notion Tuesday at the annual Isaac Asimov Memorial Debate here at the American Museum of Natural History.
Moderator Neil deGrasse Tyson, director of the museum’s Hayden Planetarium, put the odds at 50-50 that our entire existence is a program on someone else’s hard drive. “I think the likelihood may be very high,” he said. He noted the gap between human and chimpanzee intelligence, despite the fact that we share more than 98 percent of our DNA. Somewhere out there could be a being whose intelligence is that much greater than our own. “We would be drooling, blithering idiots in their presence,” he said. “If that’s the case, it is easy for me to imagine that everything in our lives is just a creation of some other entity for their entertainment.”
Your 101 guide to whether or not computers are going to murder us.
This seems like a rough time to be human: Artificial intelligences are beating us at Go, getting better at driving cars, and doing all sorts of other stuff. How much longer until they just rise up and kill us?
Longer than you might think, and though there are good reasons for caution and concern, a lot of the talk you hear about Terminator-type scenarios is excessively alarmist. Read an article on, say, the rise of robot butchers, and you’ll inevitably find commenters worrying that the system is going to go haywire and attack its human masters. Even when they’re a little joke-y, these responses tend to bear the trace of the old Luddite anxiety that machines are somehow fundamentally opposed to humanity.
If you really get into it with A.I. researchers, you’ll find that most of them aren’t really worried about murder-bots actively looking to KILL ALL HUMANS. Instead, they’re concerned that we don’t really know what we’re getting into as we rapidly engineer systems that we can barely comprehend, let alone control. It’s this concern that’s led Elon Musk—who’s supported all sorts of A.I. research—to describe artificial intelligence as an “existential threat.” He seems concerned that we may not be able to direct the forces that we’re calling into being.
On Monday, Melinda D. Anderson published an article in The Atlantic asking “Will the Push for Coding Lead to ‘Technical Ghettos’?” That is, will educational inequalities surrounding CS education mean that students of color end up in low-pay, dead-end jobs in the tech industry?
A few days later, Edsurge published its list of ed-tech trends, one of which is computer science education. In its summary of this trend, Edsurge dates the history of teaching computer science in K–12 to 1984, when the College Board first offered the Advanced Placement exam in the subject. No mention of Papert in the timeline. No mention of LOGO (which was developed in 1967).
This is how you rewrite education technology history – and rewrite it to serve a particular narrative.
On the rise of UI-less apps and why you should care about them as a designer.
A couple of months ago, I shared with my friends how I think apps like Magic and Operator are going to be the next big thing.
If you don’t know about these apps, what make them special is that they don’t use a traditional UI as a mean of interaction. Instead, the entire app revolves around a single messaging screen. These are called ‘Invisible’ and ‘Conversational’ apps, and since my initial post, a slew of similar apps came to market. Even as of writing this, Facebook is releasing M, a personal assistant that’s integrated with Messenger to help you do about anything.
If you didn’t realize how pervasive SMS has become today, think again. SMS is the most used application in the world. Three years ago, it had an estimated 4 billion active users.That was over four times the numbers of Facebook usersat the time. Messaging and particularly SMS has been slowly taking over the world. It is now fundamental to human communication, and it is why messaging apps such as WhatsApp and WeChat are now worth billions.
The biological world is computational at its core, argues computer scientist Leslie Valiant. His “ecorithm” approach uses computational concepts to explore fundamental mysteries of evolution and the mind.
He broadened the concept of an algorithm into an “ecorithm,” which is a learning algorithm that “runs” on any system capable of interacting with its physical environment. Algorithms apply to computational systems, but ecorithms can apply to biological organisms or entire species. The concept draws a computational equivalence between the way that individuals learn and the way that entire ecosystems evolve. In both cases, ecorithms describe adaptive behavior in a mechanistic way.
(2015). Constructionist Gaming: Understanding the Benefits of Making Games for Learning. Educational Psychologist: Vol. 50, Psychological Perspectives on Digital Games and Learning, pp. 313-334. doi: 10.1080/00461520.2015.1124022
A primary focus of constructionism examines learning from a personal perspective, very much in the Piagetian tradition. Papert saw the engagement with Logo programming as a way to facilitate the construction of knowledge structures and what he termed “appropriation” so that learners could make knowledge their own and begin to personally identify with it. Programming the Logo turtle in the context of a game very much makes the construct an “object-to-think-with” (Papert, 1980) linking together artifacts in the physical world (in this case, a turtle) with those representations (in this case, the rules and objects) in the mind. Papert argued that objects-to-think-with such as the Logo turtle are particularly effective at supporting appropriation because they facilitate the learner's personal identification with the object and help to construct, examine, and revise connections between old and new knowledge. By designing a game (or, on a more granular level, its procedures, algorithms, and data structures), the personal knowledge becomes public and can then be shared with others. Of course, thinking about game programs as personal objects that can be shared widely as public entities articulates a phenomenon entirely akin to the growth of Internet culture, which too is built upon the amassment of intimately personal items (e.g., photos, stories, and designs) introduced on an equally massive wider public sphere, which then takes on entirely new meanings upon this wider scale. And it connects nicely to the social dimension of constructionist gaming.
Coding is coming to all of our schools with a lot of hype, inevitably there is push back from many different quarters for a variety of reasons… In my view these push backs are uninformed. The code I know is the vanguard for modern learning, and for this reason, in my view, anyone interested in learning should take notice, and seek to understand, what is happening.
The Importance of the Learning Environment
We get so attune to curriculum and assessment as it is done in schools, we can begin to think that all learning, no matter how it occurs, produces the same results and the same outcomes. Nothing could be further from the truth.
What happens when computer science isn’t an additional class, but worked into the projects that students create in art and humanities classes? What happens when we realize that coding is a language, and as a language, expresses something?
Professional artists and designers have used coding to create visual forms of expression. There’s a community of such artists creating libraries and open-source software from their experience in computational design. These products, such as Cinder, make coding more accessible to artists looking to learn by playing around with the syntax. These artistic communities are highly professional but also supportive, embodying the participatory culture and sharing ethos of the coding community.
On October 30, we celebrated the Media Lab’s 30th anniversary with a day-long symposium, Mind, Magic & Mischief, followed by a party and alumni gathering. Highlights were tributes to Marvin Minsky and Lab co-founder Jerome Wiesner, and talks by Kofi Annan, Steve Pinker, George Church, Nolan Bushnell, Mary Lou Jepsen, and US CTO Megan Smith. The event also recognized the Lab’s 30-year collaboration with LEGO. To acknowledge this, LEGO gave us an incredible 30th birthday present: a scale model of the Media Lab complex—made out of LEGO, of course. If you’re in Cambridge, you can see it on display in our E14 lobby.
Our Knotty Objects summer symposium in July brought together a group of designers, inventors, and scholars who are merging design and technology in new and unexpected ways. Our antidisciplinary view of research made the Lab a great spot to explore the intersection of design and technology.
Teachers who work at the poorest schools are more likely to think that computer science is vital to their students’ futures, but are less likely to think their school boards agree, a new survey released Tuesday reveals.
The survey was conducted by Gallup on behalf of Google, and looks at perceptions of computer science for different groups, including students, parents, educators and school district administrators. It follows an earlier survey released in August, which looked at access to computer science courses and found that lower-income students have fewer opportunities to study the subject. However, this latest survey shows that low-income students' lack of access is not due to apathy on the part of their educators.
Twenty-one percent of teachers who work at schools where more than half of the student body qualifies for free or reduced-price lunch said they thought access to computer science is more important to a student’s future success than other elective courses, like music or art. Only 10 percent of teachers who work at schools where 25 percent or fewer students qualified for free or reduced-price lunch said the same thing.
Much like a good song, good code is all about how the individual pieces fit together.
“Some of the best musicians I know are also engineers,” (coder and musician Richard) Plom says, pointing to various coders among the vast ranks at Apple. The two pastimes, you see, aren’t as different as they might seem. “Good code—when it’s written the right way—sings,” Plom explains. “It’s like constructing a song.”
You get a glimpse of that watching a Vine video with a perfect loop. It’s music, driven by code. And in a way, itresembles code, which often include loops. But at the same time, to use Plom’s term, these Vine videos “sing”—in multiple ways. And reaching that point requires a quality found in coders and musicians and coder-musicians. As Plom describes it: “It’s a way of thinking.”
We found that users who had never used a concept were more likely to do so if they had been exposed to the concept through remixing. Although some concepts were more widely used than others, we found a positive relationship between concept use and exposure through remixing for each of the six concepts. We found that this relationship was true even if we ignored obvious examples of cutting and pasting of blocks of code. In all of these models, we found what we believe is evidence of learning through remixing.
As it’s become a buzzword (sadly), let’s have a conversation to clear up the rhetoric and get to deeper meaning. To me, as a computational scientist, the essence is what we can do while interacting with computers, as extensions of our mind, to create and discover. That’s not the popular message today.
It turns out, the original notion of computational thinking, as envisioned by Seymour Papert, already encompasses the learning I was alluding to. In turn, the popularized meaning of “computational thinking” is a shallower, less powerful idea, as I will explain.
The move didn't make sense to all the humans packed into the sixth floor of Seoul's Four Seasons hotel. But the Google machine saw it quite differently.
It was a move that demonstrated the mysterious power of modern artificial intelligence, which is not only driving one machine’s ability to play this ancient game at an unprecedented level, but simultaneously reinventing all of Google—not to mention Facebook and Microsoft and Twitter and Tesla and SpaceX. In the wake of Game Two, Fan Hui so eloquently described the importance and the beauty of this move. Now an advisor to the team that built AlphaGo, he spent the last five months playing game after game against the machine, and he has come to recognize its power. But there’s another player who has an even greater understanding of this move: AlphaGo.
When technologists describe their hotshot new system for trading stocks or driving cars, the algorithm at its heart always seems to emerge from a magical realm of Spock-like rationality and mathematical perfection. Algorithms can save lives or make money, the argument goes, because they are built on the foundations of mathematics: logical rigor, conceptual clarity, and utter consistency. Math is perfect, right? And algorithms are made out of math.
In reality algorithms have to run on actual servers, using code that sometimes breaks, crunching data that’s frequently unreliable. There is an implementation gap between what we imagine algorithms do in a perfect computational universe and all the compromises, assumptions, and workarounds that need to happen before the code actually works at scale. Computation has done all sorts of incredible things, sometimes appearing both easy and infallible. But it takes hundreds or thousands of servers working in tandem to do something as straightforward as answer a search engine query, and that is where the problems of implementation come in.
Many of Casey Reas' programmatic artworks resemble things you see in nature—tangles of leaves, daffodils, bee colonies, algae—but they’re anything but code. Computer code underpins many aspect of our lives. Usually we know exactly what we want that code to do - but what if we didn't? This is the question posed by Los Angeles software artist Casey Reas, who employs code to form abstract, bewildering, and literally unexpected creations.
Open-source, Internet-assisted farming aims for a new green revolution Is urban agriculture on the verge of an Internet-enabled revolution? According to a team of technologists at MIT, this unexpected possibility may yet emerge from a series of recent technological breakthroughs. These include the development of high-efficiency blue LED lighting, whose inventors received the 2014 Nobel Prize in Physics.
President Obama just unveiled his “Computer Science for All Initiative.” Following up on the State of the Union Address, in which he announced his intention to offer “every student the hands-on computer science and math classes that make them job-ready on day one,” the initiative includes $4billion in funding for states and $100Million directly for districts to increase hands-on K-12 computer science instruction.
If we want to get to the next great era of human ingenuity, we will absolutely need to make sure that everyone knows a little bit about the math and science that underlies today’s dominant technologies. But it is not, as President Obama believes, so they can be the labor force that drives a digital information economy. It is so that they have the critical objectivity to maintain their humanity even as they fully embrace a digital world.
The Industrialist’s Dilemma is a new course at the Stanford Graduate School of Business that runs in the Winter of 2016, In “The Industrialist’s Dilemma” at Stanford GSB this Winter, we’ll be exploring the lessons of the world’s best startups taking on legacy industries as well the fastest-adapting industrialists that are putting digital at the center of their future strategies.
Just as Marc Andreessen described that software eating the world four years ago, startups today are able to harness the power of cheaper computing, unlimited data storage, ubiquitous internet and smartphones, contract manufacturing, and improved digital experiences to attack industries that haven’t changed for decades or centuries. While for years the tech industry had been squarely focused on optimizing known tech problems –building faster search engines or a better phone– all this digital power is causing a set of entrepreneurs to explore brand new solutions to nearly every legacy industry.
For the last 150 years or so, we’ve run our cities like clockwork.
I don’t mean that as a compliment, a suggestion of flawless efficiency. Just that we’ve designed, planned and run our cities based on regulated industrial rhythms, bound to pre-digital engineering and organisations, and we still do.
We expect a rush hour at the beginning and end of work-week days, and planners intensify mass transit at these times along major arteries, usually into the middle of cities via a form of ‘hub-and-spoke’ model. Citizens must move towards the nearest nodes in that network — the bus stop, the metro station — rather than their actual origin or destination, and these must necessarily be organised along averages of demand.
These patterns are in-part derived from mass industrialisation, and its physical impacts, and the 20th century urban planner’s instinct to separate functions like retail, offices, housing and industry into different zones of the city.
These days, however, not only are we now trying to create ‘mixed-use’ urban environments, dissolving zones left, right and centre, but many of our patterns of working are fragmenting — whether that’s through zero hours contracts or the burgeoning freelance sector — as are many other patterns of living, generally.
But those clockwork patterns run deep. Few western cities look like a Lowrypainting anymore. The factories have gone, the workers have gone, the tramlines that delivered them have often gone too. Yet traffic still tends to runs along those now-buried lines, even though the route’s raison d’être has long since departed.
Coding games for kids are really about teaching the basics of logic and problem solving, said Scott Jacobsen of Madrona Venture Group, which has invested in Wonder Workshop. Technologies for kids teach how to match the analytic and creative parts of the brain, he said.
Founders of companies working on tech for kids, however, insist that the games and programs are not exclusively for kids who want to be computer scientists. Everyone, they say, will need to know how to speak to computers.
“For us, coding is not a set of technical skills but a new type of literacy and personal expression, valuable for everyone, much like learning to write,” Scratch co-founders Mitchel Resnick and David Siegel wrote in a last week. “We see coding as a new way for people to organize, express, and share their ideas.”
Many entrepreneurs agree. “It’s not that kids need to learn a particular programming language,” said Hadi Partovi, co-founder of Code.org. “It’s learning how apps work, how basic technology operates. I can’t imagine being a functioning member of society in 30 or 40 years without knowing that.”
Susan Einhorn's insight:
What is missing from many (most) of these articles is the awareness that the recognition of the importance of programming (yes, programming, not coding) as a key thinking tool and literacy skilll didn't start with code.org or the first Hour or Code or even with Scratch, but with a group of very forward-thinking people many decades earlier, most notably people like Seymour Papert, Cynthia Solomon, Wally Feurzeig. Their work inspired and helped shape much of the thinking and development we talk about today.
Software is in almost everything we touch, so the demand for software engineers is increasing exponentially. If our kids can't fill these jobs, then someone else's will and we'll have to continue to import talent.
But focusing on computer science as a gateway to good jobs would be akin to thinking about English Language Arts only in the context of script writing. It's shortsighted and completely misses the fact that coding is a new literacy that can help kids develop and achieve across every core competency.
According to a recent study by Tufts University, kids who study computer science improve transferrable skills like sequencing, which has a direct positive correlation with improved reading comprehension.
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