So, how do we become not just passengers, but possible co-designers of the space experiences that impact—or involve—us as individuals? The technologies, roadmaps, and regulatory frameworks are unfolding now, but the early stages of future service, product and policy design are still just a curious glint of light in the distance. If we don’t (or do) want a future shaped by floating sports cars or wealthy tourist flights only, now is as good a time as any to sketch other possibilities.
We reached Shadow Belmont. A place deeply familiar with shade. Shade architecture, shaded transport, sheltered time. A cityscape layered with a latticework of porches, pergolas, verandas, galleries, awnings, canopies, umbrellas and trees. From above the city looks like a desert garden. The shade of the high canopy stands on cactimorphic succulent pillars, doubling as public water sources. Closer to the ground, multi-trunked mesquite marquees diffuse light across outdoor kitchens and intimate courtyards. The ubiquitous antennae of the place mingle with soaring ocotillo vines, their cabling protected by dessicated saguaro skeletons. Solar-powered screens radiate the shadow forecast and a cooling breeze. The STA (Shade Traversal Association) maps show real-time shade developments, with roads in direct sun coloured flaming red. The droning of traffic blends into the murmur of slowly adjusting shade structures, punctuating the continuous background hum of insects, psychic noise and ambient communication.
technologists in general (and recently and in particular, the strain of technology centered around the West Coast of the United States), have operated on general idea that as technologists we’re apart from society. That, like scientists, we discover and invent new things and then it’s up to “them” — society, government, and so on — to figure out and deal with the implications and results. This argument isn’t entirely wrong: it is society and our government’s job to “figure out” and “deal with” the implications and results of technology, but it’s disingenuous of the technological class (and to be more accurate, its flag-wavers and leaders) to sidestep participation and responsiblity. In other words: nobody, not even technologists, is apart from society. Society is all of us, and we all have a responsibility to it.
To any headphone jack, all audio is raw in the sense that it exists as a series of voltages that ultimately began as measurements by some tool, like a microphone or an electric guitar pickup or an EKG. There is no encryption or rights management, no special encoding or secret keys. It’s just data in the shape of the sound itself, as a record of voltages over time. When you play back a sound file, you feed that record of voltages to your headphone jack. It applies those voltages to, say, the coil in your speaker, which then pushes or pulls against a permanent magnet to move the air in the same way it originally moved the microphone whenever the sound was recorded.
Smartphone manufacturers are broadly eliminating headphone jacks going forward, replacing them with wireless headphones or BlueTooth. We’re going to all lose touch with something, and to me it feels like something important.
The series of voltages a headphone jack creates is immediately understandable and usable with the most basic tools. If you coil up some copper, and put a magnet in the middle, and then hook each side of the coil up to your phone’s headphone jack, it would make sounds. They would not be pleasant or loud, but they would be tangible and human-scale and understandable. It’s a part of your phone that can read and produce electrical vibrations.
Luna is a WYSIWYG visual and textual, purely functional data processing language. Its goal is to revolutionize the way people are able to gather, understand and manipulate data. Luna targets domains where data processing is the primary focus, including data science, machine learning, IoT, bioinformatics, computer graphics or architecture. Each domain requires a highly tailored data processing toolbox and Luna provides both an unified foundation for building such toolboxes as well as growing library of existing ones. At its core, Luna delivers a powerful data flow modeling environment and an extensive data visualization and manipulation framework.
These are some thoughts about utopia and dystopia. The old, crude Good Places were compensatory visions of controlling what you couldn’t control and having what you didn’t have here and now — orderly, peaceful heaven; a paradise of hours; pie in the sky. The way to them was clear, but drastic. You died.
Thomas More’s secular and intellectual construct Utopia was still an expression of desire for something lacking here and now — rational human control of human life — but his Good Place was explicitly No Place. Only in the head. A blueprint without a building site.
Ever since, utopia has been located not in the afterlife but just off the map, across the ocean, over the mountains, in the future, on another planet, a livable yet unattainable elsewhere.
The list below summarizes the advice Donella Meadows was able to give after more than 30 years of working in the field of sustainability consultancy, research and education. It is an excellent set of guidelines that could help you to improve your own practice, particularly when you work in the kind of complex multi-stakeholder situations that are so commonly encountered as we try to support a systems transformation towards increased sustainability.
Leyla Acaroglu —
It’s an experimental knowledge lab that I set up three years ago to help overcome what I call the knowledge-action gap, the difference between people knowing that there are problems in the world, feeling that they want to address them, but not knowing how to take action. I really struggled a lot with the mainstream structural system of education, I did a lot of research in pedagogy and the way in which we teach and the way in which the brain works, how a lot of the experiences we have in life educate us, and how actually a lot of those experiences de-educate us.
Pynchon should be known as one of the very few foreign (white) writers who wrote responsibly about an African country, and actually improved the world by doing so. He was conscious of his privilege as a white, male author, and used this privilege in order to tell a story buried by white history: the Herero people’s genocide by German colonial forces, the first, “forgotten” genocide of the 20th century.The massacre is integral to two of Pynchon’s most famous novels, V. and Gravity’s Rainbow.
The world needs to act fast: if humans continue to emit greenhouse gases at current rates, the remaining carbon budget to reduce risk of exceeding the 2°C target will be exhausted in around 20 years. Emissions should peak by 2020 and approach zero by around 2050 if the world is serious about reducing risk. As a simple rule of thumb, this means halving global emissions every decade, which can act as a golden rule. This golden rule is a road-map to prosperity. A fossil-fuel free society is economically attractive: renewable energy sources increasingly compete with fossil fuels, even when these are priced at historic lows. Moreover, the estimated costs of inaction range from 2–10% of GDP by 2100 by some estimates, to a final invoice equivalent to a 23% collapse in global productivity.
Before the internet, publishing had been a distinction, with a limited number of people lucky, talented or wealthy enough to share ideas or images with a wide audience. After the rise of social media, publishing became a default, with non-participation the exception. There’s a problem with this rise in shared self-expression: we’ve all still got a constant and limited amount of attention available. For those creating content, this means the challenge now is not publishing your work, but finding an audience. The problem for those of us in the audience — i.e., all of us — is filtering through the information constantly coming at us.
It’s a bot that creates, owns and sells the digital art it creates without relying on humans. We are only there to help it succeed. This bot’s soul will come to live in a smart contract on Ethereum. With us guiding it, it will create a new unique artwork every week, put it up for auction and sell it: creating a unique digital, transferable edition of the art. If we do our job right, it will make better and better art over time. The humans that help it will be rewarded in turn for doing so.
Experience is interconnected and entangled. Unpredictable. It can never be fully explained. There is always something that slips beyond words. A description or a model of an interconnected world does not encompass all the complex processes of making connections.
While the sense of the moment may be one of accelerated change, there is simultaneously drag, weight and the inevitable delays of change that takes too long. Injustices perpetuated. We find ourselves in situations without an escape velocity.
Is the uncertainty we’re experiencing just a series of erratic oscillations or are we in the free fall toward something more massive? Things are collapsing, and sometimes the best thing to do is let them. Accept the gritty reality of it all.
Software 2.0 is written in neural network weights. No human is involved in writing this code because there are a lot of weights (typical networks might have millions), and coding directly in weights is kind of hard (I tried). Instead, we specify some constraints on the behavior of a desirable program (e.g., a dataset of input output pairs of examples) and use the computational resources at our disposal to search the program space for a program that satisfies the constraints. In the case of neural networks, we restrict the search to a continuous subset of the program space where the search process can be made (somewhat surprisingly) efficient with backpropagation and stochastic gradient descent. It turns out that a large portion of real-world problems have the property that it is significantly easier to collect the data than to explicitly write the program. A large portion of programmers of tomorrow do not maintain complex software repositories, write intricate programs, or analyze their running times. They collect, clean, manipulate, label, analyze and visualize data that feeds neural networks.
Automated reward systems like YouTube algorithms necessitate exploitation in the same way that capitalism necessitates exploitation, and if you’re someone who bristles at the second half of that equation then maybe this should be what convinces you of its truth. Exploitation is encoded into the systems we are building, making it harder to see, harder to think and explain, harder to counter and defend against. Not in a future of AI overlords and robots in the factories, but right here, now, on your screen, in your living room and in your pocket.
Many of these latest examples confound any attempt to argue that nobody is actually watching these videos, that these are all bots. There are humans in the loop here, even if only on the production side, and I’m pretty worried about them too.
This is a deeply dark time, in which the structures we have built to sustain ourselves are being used against us — all of us — in systematic and automated ways. It is hard to keep faith with the network when it produces horrors such as these. While it is tempting to dismiss the wilder examples as trolling, of which a significant number certainly are, that fails to account for the sheer volume of content weighted in a particularly grotesque direction. It presents many and complexly entangled dangers, including that, just as with the increasing focus on alleged Russian interference in social media, such events will be used as justification for increased control over the internet, increasing censorship, and so on. This is not what many of us want.
The rules governing when a piece of creative content enters the public domain may seem initially straightforward, but determining whether something is truly in the public domain can result in a swamp of obscure rules, strange regulations, legal complexity, and varying interpretations of exceptions.
In most countries, copyright term is based on the life of the author plus an additional set duration of protection — usually from 50 to 70 years beyond the death of the creator. In Mexico, copyright protection lasts for 100 years after the death of the author. Within Europe there have been attempts to harmonise copyright terms across the Member States for about 25 years now. In theory, the copyright duration has been harmonised to 70 years after the death of the last surviving author. In practice however, each Member State has different public domain regulations.
I don’t have hundreds of unpopular opinions on blockchain/cryptocurrency, or anything for that matter. I did manage to rant for over sixty tweets. At the suggestion of multiple people I have compiled the tweets into this post. I tried to organize them thematically as best I could.
While blockchain is the future, I do not believe the future is what we are living today. We are living among the experiments. What we see around us might be in ruins tomorrow. What we get as our future might not have been invented yet. With hopes still high and a sharp eye on the industry, I am waiting for the ultimate blockchain. Will it be Ethereum? Or NEO? Or Qtum? Or Tezos? Or something else? I don’t know. For now, I am excited to witness one of the largest shifts a human life can live through. Even if the future does not appear to be near, the future is not far either.
The TEFAF Art Market Report, Online Focus 2017 highlighted the importance of decentralised technology within the art market. Pownall’s report includes survey responses from 673 dealers regarding their views on the use of blockchain. She finds that three quarters of auction houses, one third of intermediaries and one fifth of galleries intend to ‘offer blockchain technology within the next five years’. She also finds that almost 20% of galleries, auction houses and intermediaries intend to accept payment in digital currencies in the future. Despite these ambitions, there is an absence of shared research and knowledge and a severe lack of co-ordination about blockchain solutions that would be suitable for the art ecosystem.
In the last century in particular, applause has been tamed — abstracted by the technologies of mass media, and constricted by the etiquette of high culture. Learning how to clap appropriately is an essential part of being a good citizen, whether you are applauding the speech of a dictator, or not applauding between the movements of a classical performance.
But we rarely think about why we clap in the way that we do. Applause serves multiple purposes — it gives the crowd a voice of approval (or, in its absence, rejection), it gives artists a feedback loop that they can work with or against in their performance, and it gives those in power — whether cultural entrepreneurs or machiavellian politicians — a tool they can use to turn public opinion in their favour.
In order to tell the story of how applause has been tamed, we first have to notice how it works in our culture at the moment. Because we tend to think of applause as a natural response, the best way to notice it is by looking at what happens when applause goes wrong.
This new faith has emerged from a bizarre fusion of the cultural bohemianism of San Francisco with the hi-tech industries of Silicon Valley. Promoted in magazines, books, TV programmes, websites, newsgroups and Net conferences, the Californian Ideology promiscuously combines the free-wheeling spirit of the hippies and the entrepreneurial zeal of the yuppies. This amalgamation of opposites has been achieved through a profound faith in the emancipatory potential of the new information technologies. In the digital utopia, everybody will be both hip and rich.
Not surprisingly, this optimistic vision of the future has been enthusiastically embraced by computer nerds, slacker students, innovative capitalists, social activists, trendy academics, futurist bureaucrats and opportunistic politicians across the USA. As usual, Europeans have not been slow in copying the latest fad from America. While a recent EU Commission report recommends following the Californian free market model for building the information superhighway, cutting-edge artists and academics eagerly imitate the post human philosophers of the West Coast’s Extropian cult.[3] With no obvious rivals, the triumph of the Californian Ideology appears to be complete.
So how do we spot these accounts in the wild? Following are a number of traits we’ve found in our research. As you might expect, many accounts that are not bots or sockpuppets exhibit some of these traits. None of them are foolproof. But the more of these traits an account displays, the more likely it is to be a disinformation account. In our research, we’ve found it far more helpful to look for evidence of these traits in a large collection of tweets, rather than trying to come up with discrete lists of bots, sockpuppets, trolls, and regular users. It’s often these traits that are most dangerous, and it’s these traits that we can look out for when engaging information online ― and when sharing information ourselves. It is also worth highlighting that many of the traits exhibited by bots and sockpuppets are pulled directly from tactics used in online harassment.
The Modernist master Fernando Pessoa’s work remained largely unnoticed during his lifetime. He left behind a chest full of writing that would be later known to many as The Book of Disquiet. The book has been deemed an “autobiography” and a “diary,” but it’s equally a novel or an essay collection or even a kind of pre-internet codex blog. Pessoa ruminates about pretty much everything, often entering enlightening and sorrowful spaces while battling life’s eternal questions. Recently released by New Directions with a brand new translation, The Book of Disquiet is in its most complete form ever.
Forest Watcher was first developed by the Jane Goodall Institute (JGI), Google, Touch Lab and Global Forest Watch to give forest rangers and local communities access to up-to-date satellite data for forest monitoring offline. This provided a great opportunity to inform patrols as not everyone has access to the internet — especially when they are deep inside a vast, thick rainforest. However, with new forest loss satellite products such as weekly GLAD and fire alerts, the app needed an update. To address this, we’ve built a new version that builds on the lessons learnt from the first version and continues to provide offline access to the latest forest data.
Archetypes are recurring patterns of behavior that give insights into the structures that drive systems. They offer a way of deciphering systems dynamics across a diversity of disciplines, scenarios, or contexts. Think of these archetypes as the storylines of systems in the world. Just as you can identify the same formula for a romcom or a thriller in a Hollywood film, these archetypes help systems thinkers see behaviors and flows in more concrete terms. Basically they offer insights into universal behaviors across different system scenarios.
Archetypes rely on heuristics, which are mental shortcuts that we all use to make sense of the world. We use archetypes to help shift our perspective of a problem from a mental model of blame, to one of curiosity and constant inquiry.
The central tension in camouflage is between being seen, and going unseen. With the discussion about what it is that constitutes national identity currently even being debated as part of the formation negotiations for the new Dutch coalition government, the core irony of this project looks to remain relevant for quite some time. If a Dutch identity exists, how would a camouflage for it function? Or more importantly, why would anyone want or need to conceal themselves with it in the first place? What you are hiding from? How you want to be seen?
The web has turned out to be just another communication tool to reflect the good and bad of society. No more, no less. The good in the world is still mostly shaped by governments, regulation, NGOs, the UN, the EU (GDPR), philanthropists and volunteer organisations. Throughout the two day conversation, I felt people were disappointed the web hadn’t been able to live up to its perceived almost-socialist-but-ultimately-neo-liberal promise. Many said they wanted to engage with governments more. Many talked about open data for cities. Mostly, it was unclear what exactly the web could do to address ISIS, sexism, racism, violence, addiction. Because it can’t. The web has become as useful or useless as people want it to be. No more, no less.
In Estonia, we have another trick up in our sleeves: we can use our rich culture of linguistics and mythology as a vehicle for understanding more complex technological issues. For example, in Estonian mythology we have a character called kratt, a creature which has existed in our cultural space for hundreds of years and which is composed of a number of unique features. When the owner acquires from the devil a soul for its kratt (in modern tech talk this mean algorithm), the kratt begins to serve its master. From a communication point of view, the “kratt” narrative is useful because every Estonian knows this story. Kratt’s are something that society understands;
AI is something that is complex and difficult to understand. From a technological point of view, the kratt character has exactly the same features as AI. When the Czech writer Čapek invented the word ‘robot’ in 1920 the inspiration came from the Slavic language word ‘robota’ meaning forced labourer. Yes, a robot is something made to fulfil certain tasks, but we can also say that a kratt is a robot with super powers and thus the legal representative rights.
It wasn’t until I left broadcasting that I realised how complex and controversial the words ‘story’ and ‘audience’ really were. I called my company ‘Storythings’ for two reasons - one was because I’d been running a conference called The Story for a few years that was pretty much the genesis of the company, and the second was because I was more interested in stories than I was in technology. I’m fascinated by how we tell stories now, and the new relationships we can have with audiences across all sorts of interesting contexts and platforms.
But when I started talking to clients, I was surprised by how those two words - Story and Audience - meant completely different things to different people. Stories seemed to be the hot new idea in marketing, and every brand wanted to know how to tell their story, or to hear their customers’ stories. Transmedia gurus were trying to convince us that stories were many-tentacled hydras, performing complexly choreographed dances to lure fans into their narratives.
But no-one outside of broadcasting really used the word ‘audience’. There were customers, fans, users, subscribers, followers, networks, communities and participants. Audiences were points in a cloud of big data, or a constantly updated Chartbeat report. Audiences were presented as infographics, or studied as psychological experiments.
Alongside the familiar patterns of mainstream attention, there are a huge number of new patterns that could only exist in digital culture. Some of these patterns are very slow, with attention accruing over months or years, as social recommendation or small groups of fans gradually accrue around content. Some are extremely fast, synchronising audiences’ attention around a piece of culture within days, before moving on just as quickly. Some are driven by deliberate plans, orchestrated between broadcast channels and social media. Some emerge via the organic connections of lots of smaller drivers, from blogs and niche channels to SEO and twitter accounts.
But, regardless of the pattern itself, the difference is that they’re Spiky — there are no technical or economic constraints keeping the spotlight in one place anymore, so attention can move on as quickly as it arrived. This is the major shift that we are missing when we are nostalgic for the 20th century. We’re only just beginning to learn what culture looks like in spiky networks, and only just beginning to invent the companies and institutions that can survive long enough to support and invest in culture in this landscape.
That something else, call it imagination or call it dreaming, does not require validation with immediate reality. The closest incarnation we have today is the generative adversarial network (GAN). A GAN consists of two networks, a generator and a discriminator. One can consider a discriminator as a neural network that acts in concert with the objective function. That is, it validates an internal generator network with reality. The generator is an automation that recreates an approximation of reality. A GAN works using back-propagation and it does perform unsupervised learning. So perhaps unsupervised learn doesn’t require an objective function, however it may still need back-propagation.
But perhaps 5% of designers and engineers have a different view — they sense that users have interests or aims which go beyond their immediate goals or apparent preferences. Thus a product which helps with goals, or which satisfies preferences, could nonetheless be a waste of a user’s time. And a user could — despite responding to many emails and seeing many photos — eventually regret using such a product, because the product derailed a deeper concern the user has.
What is even more important to a person than their current goals or preferences? The process of refining, discovering, and clarifying those goals and preferences.
Foresight is, of course, more than single step. As part of a well-rounded analysis of possible futures, the step of mapping context is critical and why we give it the attention it deserves as part of a broader curriculum. Pairing powerful sensemaking tools with ways of bringing future concepts to life are the core of what Future Design provides. Beyond providing a platform to learn about emerging drivers of change, Future Design can equip students with tools to:
Identify possibilities and risks upstream, before an innovation lands,
Understand the impacts and connections between issues and innovations,
Uncover surprising future issues that point toward challenges in the present; and
Futureproof design by anticipating change in different contexts and scenarios.
Algorithmic music composition has developed a lot in the last few years, but the idea has a long history. In some sense, the first automatic music came from nature: Chinese windchimes, ancient Greek wind-powered Aeolian harps, or the Japanese water instrument suikinkutsu. But in the 1700s music became “algorithmic”: Musikalisches Würfelspiel, a game that generates short piano compositions from fragments, with choices made by dice.
Dice games, Markov chains, and RNNs aren’t the only ways to make algorithmic music. Some machine learning practitioners explore alternative approaches like hierarchical temporal memory, or principal components analysis. But I’m focusing on neural nets because they are responsible for most of the big changes recently. (Though even within the domain of neural nets there are some directions I’m leaving out that have fewer examples, such as restricted Boltzmann machines for composing 4-bar jazz licks, short variations on a single song, or hybrid RNN-RBM models, or hybrid autoencoder-LSTM models.)
The German systems scientist, Professor Frederick Vester (2004: 36–37), identified a number of common mistakes that occur as teams are asked to intervene in or ‘manage’ complex dynamic systems. Vester’s insights drew on a series of experiments by the psychologist Dietrich Dörner who had challenged various transdisciplinary teams of 12 different specialists to improve the overall system and infrastructure design of a fictitious country in the developing world. A computer program modelled the impact of their strategies over a century of repeated cycles of interventions. The focus of the study was how teams of experts approach problem-solving, planning and systems interventions. Vester’s analysis of Dörner’s work provides the basis for a useful list of questions that we can ask ourselves to avoid the most common mistakes in dealing with complex systemic issues.
For a decade we have experimented with different approaches to managing the studio as a shared living-and-working space. In 2016 we took some distance from the day-to-day management and production to observe our work from a more detached perspective. By the end of the year it became clear that FoAM bxl needed to become lighter and more mobile. […] In light of the changing nature of our activities we decided that we no longer needed such a large space, and that we would move out of the Koolmijnenkaai studio, no matter how beautiful and unique it may be. We remain grateful to have been able to inhabit the space for as long as we did, but it had become time to move on.
Addressing mistrust in media requires that we examine why mistrust in institutions as a whole is rising. One possible explanation is that our existing institutions aren’t working well for many citizens. Citizens who feel they can’t influence the governments that represent them are less likely to participate in civics. Some evidence exists that the shape of civic participation in the US is changing shape, with young people more focused on influencing institutions through markets (boycotts, buycotts and socially responsible businesses), code (technologies that make new behaviors possible, like solar panels or electric cars) and norms (influencing public attitudes) than through law. By understanding and reporting on this new, emergent civics, journalists may be able to increase their relevance to contemporary audiences alienated from traditional civics.
We had lunch earlier this week, and we spent an hour getting to know each other — our families, our paths to the jobs we hold today, our feelings about our alma mater. Basically, we spent an hour becoming friends. I like the guy. I’m going to have lunch with him again, and I’m going to pay the next time. All of which made it harder to ask the question I needed to ask: Why Trump?
We already know that many people become e-residents simply because they are fans of our country, our technology and our ideas, and being an e-resident enables them to show their support. A government-supported ICO would give more people a bigger stake in the future of our country and provide not just investment, but also more expertise and ideas to help us grow exponentially.
As an investment opportunity, estcoins could benefit Estonia and be attractive to investors from the day it is launched. As with e-Residency however, the longer term opportunities could be far greater and possibly beyond anything we can currently comprehend. In time, estcoins could also be accepted as payment for both public and private services and eventually function as a viable currency used globally. By using our APIs, companies and even other countries could accept these same tokens as payment. It will also be possible to build more functions on top of the estcoins and use them for more purposes, such as smart contracts and notary services.
when we look at religion and, to some extent ancestral superstitions, we should consider what purpose they serve, rather than focusing on the notion of “belief”, epistemic belief in its strict scientific definition. In science, belief is literal belief; it is right or wrong, never metaphorical. In real life, belief is an instrument to do things, not the end product. This is similar to vision: the purpose of your eyes is to orient you in the best possible way, and get you out of trouble when needed, or help you find a prey at distance. Your eyes are not sensors aimed at getting the electromagnetic spectrum of reality. Their job description is not to produce the most accurate scientific representation of reality; rather the most useful one for survival.
There’s a good research report that was just published. It’s called “Defending Internet Freedom through Decentralization: Back to the Future?” It’s by Chelsea Barabas, Neha Narula, and Ethan Zuckerman, under the auspices of The Center for Civic Media & The Digital Currency Initiative at the MIT Media Lab. What is decentralization? Take the web: Anyone can set up a web page and link to any other web page. That’s decentralized. Anyone can make a search engine to find those web pages. That’s centralized. The search engine can add blogging. That’s Google + Blogger. Now it’s both a publisher and a search engine. It has more power. Decentralized things are harder to manage and use. Centralized things end up easy to use and make money for relatively few people. The web is inherently decentralized, which has made it much easier for large companies to create large, centralized platforms. It’s a paradox and very thorny.
China is the world’s biggest consumer of raw materials. Each year it buys billions of tonnes of crude oil, coal and iron ore. But there is one commodity market in which the country may soon play a less dominant role: waste. Last month China told the World Trade Organisation that by the end of the year, it will no longer accept imports of 24 categories of solid waste, as part of a government campaign against “foreign garbage”. Government officials say restricting such imports will protect the environment and improve public health. But the proposed ban will threaten billions of dollars in trade and put many Chinese recyclers out of business. Why is Beijing so eager to trash its trade in rubbish?
wo summers ago, Courtenay Cotton led a workshop on machine learning that I attended with a New York–based group called the Women and Surveillance Initiative. It was a welcome introduction to the subject and a rare opportunity to cut through the hype to understand both the value of machine learning and the complications of this field of research. In our recent interview, Cotton, who now works as lead data scientist at n-Join, once again offered her clear thinking on machine learning and where it is headed.
“I always blamed Wired magazine and the investment ethos for changing the internet from an anything-can-happen, new human-potential movement that was represented so well by MONDO 2000, into the same old expansion of capital through IPOs and digital companies. I hate to even term it like this, but what went wrong? Why didn’t we get the whole everything changing at once for the human better that we were all imagining up in the Berkeley hills in the MONDO 2000 living room?”
Recently, city officials from London to Manchester to Amsterdam and Melbourne have been wrestling with the appearance of Singaporean oBike and similar bike-sharing schemes in their streets. These dockless variants of the public, pay-by-use bike models being launched in major cities around the world allow users to pick up, pay for, then leave a bike anywhere within an operating city, with no organized storage system per se, just free range. As seamless as this might sound in theory, in practice it’s causing headaches that may be yet another signal of a complicated mobility future that’s emerging as societies transition to new mobility models. New public two-wheeled platforms, like many complex systems, carry cultural values, and those carried in some of the latest bike systems speak to what we may experience in an autonomous four-wheeled future.
As was the case with the mobile revolution, and the web before that, ML will cause us to rethink, restructure, displace, and consider new possibilities for virtually every experience we build. In the Google UX community, we’ve started an effort called “human-centered machine learning” (HCML) to help focus and guide that conversation. Using this lens, we look across products to see how ML can stay grounded in human needs while solving them in unique ways only possible through ML. Our team at Google works with UXers across the company to bring them up to speed on core ML concepts, understand how to integrate ML into the UX utility belt, and ensure ML and AI are built in inclusive ways. We’ve developed seven points to help designers navigate the new terrain of designing ML-driven products. Born out of our work with UX and AI teams at Google (and a healthy dose of trial and error), these points will help you put the user first, iterate quickly, and understand the unique opportunities ML creates.
Don’t expect Machine learning to figure out what problems to solve
Ask yourself if ML will address the problem in a unique way
Fake it with personal examples and wizards
Weigh the costs of false positives and false negatives
Bob’s thesis was that he — and all of us really — existed in conditions of mentally mutilating, systematic oppression. We didn’t know that, because we didn’t dare name our oppressor, any more than Eastern European dissidents living at that time could boldly name the Communist Party and the KGB as the authors of their daily distress. But our oppressor was “work.”
“No one should ever work.” Bob was an essayist of rather broad interests, but this was the flagpole of the Black ideology. No Work. His analysis studied the actual deprivations of our freedom. Not the power-structures within various states, or the rights allegedly guaranteed by constitutions, or the effects of racial or gender prejudice, but really, just, life: the lived hours of your precious days. Where did your lifetime actually go? In the “free world,” most people spent their lifetime working. They were “free” to work.
That’s what this book is about. It is all about how “work” is much better conceived as a malignant, destructive condition called “forced labor.” It’s not that people want to “work,” by their nature. No, they’re cajoled into work by moral suasion, then kept confined within their work by large, cumbersome, irrational, spirit-crushing, economic, legal and police frameworks.
When media start to explode in your hands, it deserves a description. When it causes airplane evacuations, general panic and hysteria, it warrants an examination. When it quietly dies in your pocket before the end of an eight hour work day just like the other two billion smartphones, it deserves an explanation. It is reasonable to believe that a ‘Thermal Runaway’ event is far more spectacular than a quiet smartphone death. Leakages take place, fire and toxic chemicals are involved, possibly leading to personal bodily injury. It can be traumatic. Thermal Runaway is today one of the prime modes of battery failure. Chemical reactions within raise its internal temperature, and if not dissipated, the temperature keeps rising that will further accelerate the reactions causing even more heat to be produced, eventually resulting in an explosion. Especially a Lithum-ion cell above a certain temperature, its internal chemical reactions out of control, will explode.
The context for public innovation is changing rapidly – where as the mainstream discourse over the last 5 years was focused on service & experience redesign in a digital age, increasingly we are recognising the need for a more foundation shift in the creation & nature of public good itself and thereby a necessary shift also in the nature of the public institutional infrastructure itself.
In their book Ecological Design, Sim Van der Ryn and Stuart Cowan introduce the concept of ‘scale-linking’. They argue that since we traditionally have studied the world using the language, metaphors and tools of a single discipline at a time, we have been predisposed to “seeing process on a single scale”. […] Van der Ryn and Cowan argue that fractal geometry provides a tool to study the geometry of scale linking, as it helps to connect remarkable ranges of scale “from twig to tree, from rivulet to watershed.”141 They see our failure not to pay attention to scale-linking and therefore not to match the human flows of energy and materials to the limits of a particular landscape as a critical cause of the current environmental crisis.
From the Australian government’s new “data-driven profiling” trial for drug testing welfare recipients, to US law enforcement’s use of facial recognition technology and the deployment of proprietary software in sentencing in many US courts … almost by stealth and with remarkably little outcry, technology is transforming the way we are policed, categorized as citizens and, perhaps one day soon, governed. We are only in the earliest stages of so-called algorithmic regulation — intelligent machines deploying big data, machine learning and artificial intelligence (AI) to regulate human behaviour and enforce laws — but it already has profound implications for the relationship between private citizens and the state.
By his own account, Wallace-Wells (DWW from here on out) wrote “The Uninhabitable Earth” to frighten people out of their complacency and to inspire them to clamor loudly for immediate action to halt climate change in its petrifying tracks. Yet instead of welcoming DWW as an ally, some climate scientists attacked him, roundly criticizing his article for supposedly inspiring paralyzing sense of doom in its readers and, more importantly, for lacking scientific credibility. In a lengthly post on Climate Feedback — a site that publishes scientific assessments of representations of climate change in the popular press — these scientists condemned DWW for making factual errors, for exaggerating the projected impacts of unmitigated climate change, and for downplaying the low probability of those impacts occurring even under the high-emissions “business as usual” path that we are currently on.
Given this trend of rising corporate and central banking interest in blockchain technology, it’s inevitable that the first widespread mainstream adoption of blockchain and cryptocurrency will be driven primarily by the existing status quo and power brokers. […] Business models which operate on artificial scarcity simply cannot exist alongside a reality of public blockchains. Even if a group did attempt to deploy a for-profit protocol on a public blockchain, the code by default is opensource and thus it’s trivial to copy the code, lower the fee and then redeploy. Public blockchains are owned by nobody, controlled by nobody and can never be shutdown. Smart contracts can be owned by nobody, controlled by nobody, and execute as coded every time. The result is a blockchain commons; a universal common resource which renders old-world business models obsolete, and ushers in a new foundational paradigm on which to create value for all of humanity.
Liu Xiaobo, who has died after eight years in jail, despite being awarded a Nobel Peace Prize, was a complex human being, but he was bold, an intellectual, and in China he was a threat because he understood that civil society can organize against corruption and autocracy. Beijing released him from jail, not for the medical treatment he deserved, but simply to die. In other words, he was murdered by a murderous regime. It is time for the world to ask itself, are we accomplices, do we appease this, or do we stand up against so-called Chinese values?
How do you build a complex logistic system that collects, at national scale, the country-wide harvest, on a developing country, with little or no good data and uneven roads conditions?
To know the harvest needs, we need to know the harvest volume, timing and road access. To know these, we need good road maps (we will use OSM), and a custom routing engine (OSRM, that runs on top of OSM) to guide our loaded trucks (“DCM”s, a type of truck). That means we will need JOSM to improve OSM, and also QGIS to visualize the harvest and support the decision making. To assist on the mapping we use the free-tier of the commercial service MAPBOX (that pulls OSM data), as well as Digital Globe (DG) satellite images, and processed data from our corporate management tool (RMT) — which has information such a farmer locations, GPS traces and tree phenology data — . Then, to prioritize the tracing, to make statistics of the logistics and to estimate the harvest, we will need to do some data science. We will be using PYTHON, running on JUPYTER notebooks for documentation and clarity. To register and managed the knowledge we create, and to collaborate among the member of the team, we will use GIT and we will back it up on GITHUB, where we also do file progress and Issues.
In a recent Future Design Intensive at the Dubai Future Academy, one [team] focused on Health futures, and one on Energy futures, had just this experience. From a health point of view, climate change is likely to have a range of potentially negative impacts: increased epidemics due to ecosystem disruption, increased deaths from temperature extremes and destructive weather, threats from dislocation of populations and resources, a rise in stress due to these disruptions, and more. From an energy point of view, climate change is a driver for a more rapid transition to sustainable energy production, a spur to innovation, but also a resource and infrastructure disrupter via flooding, sandstorms and other environmental swings. The implications for both teams have overlaps and connections, but also significant differences.
An over-simplified and dangerously reductive diagram of a data system might look like this
Collection → Computation → Representation
Whenever you look at data — as a spreadsheet or database view or a visualization, you are looking at an artifact of such a system. What this diagram doesn’t capture is the immense branching of choice that happens at each step along the way. As you make each decision — to omit a row of data, or to implement a particular database structure or to use a specific colour palette you are treading down a path through this wild, tall grass of possibility. It will be tempting to look back and see your trail as the only one that you could have taken, but in reality a slightly divergent you who’d made slightly divergent choices might have ended up somewhere altogether different. To think in data systems is to consider all three of these stages at once, but for now let’s look at them one at a time.
The last ten years have been an important, formative period for the revival of social innovation, we have seen a new generation of actors contribute to the renewal of our societal goods. The work of the Young Foundation, Nesta, McConnell foundation, MaRS, Big Society Capital, SIX, TACSI, Impact Hubs and too many others to mention have been critical in seeding this question and driving its renewal globally.
Much of the work, has been focused on prototyping, understanding where the opportunity for change is and testing out micro additions or addressing edge failures in the welfare model — be it public, private or civic. Modest beginnings, and rightly so. Thereby, the work to date has largely been limited to relatively small scale interventions — tinkering & fixing at the very edges – the so called market or public service delivery failings ( social innovation projects to date have been driven largely by black swan procurement). Simultaneously and slowly over that period the sector has become stuck in the hope that “a theory of scale and impact” borrowed from the VC world and the Silicon Valley start-up landscape would be its structured salvation to societal impact.
This is not to decry an age of testing and discovery but it is also important to collectively recognise we have not gone after and meaningfully challenged mainstream social institutional infrastructure and its associated outcomes — which absorbs not just 100,000s of pounds through, but in the orders of Billions. As a community we have also failed to move any significant chunk of resource that the government allocates to military, technology or business innovation, into social innovation and the everyday services and social structures we most rely on.
The MinION costs $1,000 and is the size of a candy bar. It connects to a laptop computer’s USB port. To have it read a DNA sample, you use a micropipette to drop a “DNA library” (more on that in a minute) through a millimeter-sized opening on the MinION. Inside the device are nanopores, cones just over a billionth of a meter wide, placed in a membrane. A steady ion current flows through these nanopores. Since each nucleotide (A, T, C or G) has a unique molecular makeup, each one is shaped a little differently. The unique shape passing through the pore interrupts the ion current in a specific way. Just as we can infer a shape by analyzing its shadow on a wall, we can infer a nucleotide’s identity from the disturbances it causes to the ion current. This is how the device converts bases to bits that stream into a computer.
The first step in codifying a music is always difficult. Mostly because it’s not that simple. Artists are individuals, and, while many of them use the same programs, plug-ins, etc. their level of expertise can fool you into thinking that they’re doing something entirely different than the next person. Fetty Wap doesn’t sound like Future for several reasons: the first being that Future has been doing that style of music for far longer than Fetty, the second being that he’s an originator of it, the third being that he’s from the south, and fourth because they’re totally different human beings. But what can be said for certain…the style of music that they make is the same. How so?
The first step in codifying a music is always difficult. Mostly because it’s not that simple. Artists are individuals, and, while many of them use the same programs, plug-ins, etc. their level of expertise can fool you into thinking that they’re doing something entirely different than the next person.
Fetty Wap doesn’t sound like Future for several reasons: the first being that Future has been doing that style of music for far longer than Fetty, the second being that he’s an originator of it, the third being that he’s from the south, and fourth because they’re totally different human beings.
But what can be said for certain…the style of music that they make is the same. How so?
Value production is inherently networked. Therefore, in order to thrive, it needs an architecture as granular, scalable, and flexible as possible in order to accommodate the kinds of diverse applications and interactions that will, in turn, support its self-organization. Here at the Economic Space Agency, we want to build an ecosystem in which everyone can launch and participate in crowdsales, and exchange tokens without breaking the network. For these reasons we are building GRAVITY: a new common infrastructure for the crypto-economy. As mentioned in our previous post, GRAVITY is an open source, general purpose computing fabric based on an object-capability paradigm. The logical decentralization that this affords introduces important innovations in terms of scalability and speed, and also the possibility to host on-chain solutions for multi-blockchain integration.
“We’re still trying to figure out what time is,” Gleick said. Time travel stories apparently help us. The inventor of the time machine in Wells’s book explains archly that time is merely a fourth dimension. Ten years later in 1905 Albert Einstein made that statement real. In 1941 Jorge Luis Borges wrote the celebrated short story, “The Garden of Forking Paths.” In 1955 physicist Hugh Everett introduced the quantum-based idea of forking universes, which itself has become a staple of science fiction.
“Time,” Richard Feynman once joked, “is what happens when nothing else happens.” Gleick suggests, “Things change, and time is how we keep track.” Virginia Woolf wrote, “What more terrifying revelation can there be than that it is the present moment? That we survive the shock at all is only possible because the past shelters us on one side, the future on another.”
“Enjoy the present. Don’t waste your brain cells agonizing about lost opportunities or worrying about what the future will bring. As I was working on the book I suddenly realized that that’s terrible advice. A potted plant lives in the now. The idea of the ‘long now’ embraces the past and the future and asks us to think about the whole stretch of time. That’s what I think time travel is good for. That’s what makes us human — the ability to live in the past and live in the future at the same time.”
It might seem counter-intuitive, but Coleridge’s famous line from the Ancient Mariner could also apply to the desert. Even in some of the driest places on earth, the air holds thousands of litres of fresh water that have remained tantalisingly inaccessible. Until now. Scientists at MIT and the University of California at Berkeley have created a device that can suck water from the air. Even better: it’s solar-powered. So, even in the most remote, arid deserts it can harvest drinking water from the atmosphere.
Over at Superflux, our work investigating potential and plausible futures, involves extensively scanning for trends and signals from which we trace and extrapolate into the future. Both qualitative and quantitative data play an important role. In doing such work, we have observed how data is often used as evidence, and seen as definitive. Historical and contemporary datasets are often used as evidence for a mandate for future change, especially in some of the work we have undertaken with governments and policy makers. But lately we have been thinking if this drive for data as evidence has led to the unshakeable belief that data is evidence.
As the great German theologian Josef Pieper argued, for most of history philosophers and theologians treated overwork as a moral failing. The Stoic philosopher Seneca, for example, made a distinction between leisure and idleness; and importantly, people who were “out of breath for no purpose, always busy about nothing” were, in Seneca’s view, guilty of the worst kind of idleness. Because it occupies our time and feels like accomplishment, but actually produces very little and gives us little opportunity to learn about ourselves, this kind of busyness was to be avoided. As Pieper put it, in this vision leisure “is not a Sunday afternoon idyll, but the preserve of freedom, of education and culture, and of that undiminished humanity which views the world as a whole.” This is not to say that work was something to be avoided. Stoics like Seneca saw work as essential, as one of the things that made life meaningful. But in order to become our best selves, they argued, it was also necessary to take the time to reflect on our lives and choices — and that required both time and an “inward calm” that let us see ourselves and the world clearly.
The next step takes the logic further: not only stealing from the rich and giving to the poor (like Robin Hood did), but exploring, building new ecologies, new ecosystems, new universes, new possibilities, new worlds of value. For this purpose the Robin Hood hydra grew a new head: a start-up company Economic Space Agency, Inc. (ECSA). Economic Space Agency builds tools with which we can create economic space — not only to distribute something existing or produced in a pre-existing space, but to reorganize/rebuild the space itself. Two trends are converging and making open source economy possible: the moldability and plasticity of financial technologies and the decentralization and disintermediation provided by distributed ledgers. ECSA’s DNA contains all these things: hard core research (the team has published over 25 books), direct engagement with the power of art to create unforeseen (economical, social, political, financial, incorporeal) processes, financial first-in-the-world inventions (such as a hedge fund as a coop, and asset-backed cryptoequity), experimental hands-on attitude and an intimate lived experience of how the financial and the social co-determine each other.
For a hundred years, in an Italian palazzo transplanted to the shores of a Swedish lake, the Sigtuna Foundation has been hosting conversations where people from different worlds meet — artists, scientists, theologians, poets. So it seems an appropriate location for the meeting where I’ve spent the past two days, called by Kevin Anderson, professor of climate leadership at Uppsala University, and known (among other things) for being “the climate scientists who doesn’t fly”. At his invitation, the Centre for Environment and Development Studies at Uppsala (CEMUS) brought a group of twenty of us together to ‘develop and collate insights from the social sciences, humanities and the arts, with the purpose of eliciting a richer picture of the challenges facing rapid societal transformation’ to have a chance of reaching the commitment to limit global warming to 2° made at the Paris COP.