Daily Archives: March 8, 2017

Behnaz Farahi Breathing Wall II

This vision of the future architect was imagined by engineer and inventor Douglas Engelbart during his research into emerging computer systems at Stanford in 1962. At the dawn of personal computing he imagined the creative mind overlapping symbiotically with the intelligent machine to co-create designs. This dual mode of production, he envisaged, would hold the potential to generate new realities which could not be realized by either entity operating alone. Today, self-learning systems, otherwise known as artificial intelligence or AI, are changing the way architecture is practiced, as they do our daily lives, whether or not we realize it. If you are reading this on a laptop or tablet, then you are directly engaging with a number of integrated AI systems, now so embedded in our the way we use technology, they often go unnoticed.

As an industry, AI is growing at an exponential rate, now understood to be on track to be worth $70bn globally by 2020.This is in part due to constant innovation in the speed of microprocessors, which in turn increases the volume of data that can be gathered and stored. But dont panicthe artificial architect with enhanced Revit proficiency is not coming to steal your job. The human vs. robot debate, while compelling, is not so much the focus here but instead how AI is augmenting design and how architects are responding to and working with these technological developments. What kind of innovation is artificial intelligence generating in the construction industry?

Assuming you read this as a non-expert, it is likely that much of the AI you have encountered to this point has been weak AI, otherwise known as ANI (Artificial Narrow Intelligence). ANI follows pre-programmed rules so that it appears intelligent but is in effect a simulation of a human-like thought process. With recent innovations such as that of Nvidias microchip in April 2016, a shift is now being seen towards what we might understand as deep learning, where a system can, in effect, train and adapt itself. The interest for designers is that AI is, therefore, starting to apply itself to more creative tasks, such aswriting books, making art, web design, or self-generating design solutions, due to its increased proficiency in recognizing speech and images. Significant AI winters', or periods where funding has been hard to source for the industry, have occurred over the last twenty years, but commentators such as philosopher Nick Bostrom now suggest we are on the cusp of an explosion in AI, and this will not only shape but drive the design industry in the next century. AI, therefore, has the potential to influence the architectural design process at a series of different construction stages, from site research to the realization and operation of the building.

1. Site and social research

By already knowing everything about us, our hobbies, likes, dislikes, activities, friends, our yearly income, etc., AI software can calculate population growth, prioritize projects, categorize streets according to usage and so on, and thus predict a virtual future and automatically draft urban plans that best represent and suit everyone. -Rron Beqiri on Future Architecture Platform.

Gathering information about a project and its constraints is often the first stage of an architectural design process, traditionally involving traveling to a site, perhaps measuring, sketching and taking photographs. In the online and connected world, there is already a swarm-like abundance of data for the architect to tap into, already linked and referenced against other sources allowing the designer to, in effect, simulate the surrounding site without ever having to engage with it physically. This information fabric has been referred to as the internet of things. BIM tools currently on the market already tap into these data constellations, allowing an architect to evaluate site conditions with minute precision. Software such as EcoDesigner Star or open-source plugins for Google SketchUp allows architects to immediately calculate necessary building and environmental analyses without ever having to leave their office. This phenomenon is already enabling many practices to take on large projects abroad that might have been logistically unachievable just a decade ago.The information gathered by our devices and stored in the Cloud amounts to much more than the material conditions of the world around us

The information gathered by our devices and stored in the Cloud amounts to much more than the material conditions of the world around us. Globally, we are amassing ever-expanding records of human behavior and interactions in real-time. Personal, soft data might, in the most optimistic sense, work towards the socially focused design that has been widely publicized in recent years by its ability to integrate the needs of users. This approach, if only in the first stages of the design process, would impact the twentieth-century ideals of mass production and standardization in design. Could the internet of things create a socially adaptable and responsive architecture? One could speculate that, for example, when the population of children in a city crosses a maximum threshold in relation to the number of schools, a notification might be sent to the district council that it is time to commission a new school. AI could, therefore, in effect, write the brief for and commission architects by generating new projects where they are most needed.

Autodesk. Bicycle design generated by Dreamcatcher AI software.

2. Design decision-making

Now that we have located live-updating intelligence for our site, it is time to harness AI to develop a design proposal. Rather than a program, this technology is better understood as an interconnected, self-designing system that can upgrade itself. It is possible to harness a huge amount of computing power and experience by working with these tools, even as an individual as Autodesk president Pete Baxtertold the Guardian: now a one-man designer, a graduate designer, can get access to the same amount of computing power as these big multinational companies. The architect must input project parameters, in effect an edited design brief, and the computer system will then suggest a range of solutions which fulfill these criteria. This innovation has the potential to revolutionize how architecture is not only imagined but how it is fundamentally expressed for designers who choose to adopt these new methods.

I spoke with Michael Bergin, a researcher at Project Dreamcatcher at Autodesks Research Lab, to get a better understanding of how AI systems are influencing the development of design software for architects. While their work was initially aimed at the automotive and industrial design industries, Dreamcatcher now is beginning to filter into architecture projects. It was used recently to develop The Livings generative design for Autodesk's new office in Toronto and MX3Ds steel bridge in Amsterdam. The basic concept is that CAD models of the surrounding site and other data, such as client databases and environmental information, are fed into the processor. Moments later, the system outputs a series of optimized 3D design solutions ready to render. These processes effectively rely on cloud computing to create a multitude of options based on self-learning algorithmic parameters. Lattice-like and fluid forms are often the aesthetic result, perhaps unsurprisingly, as the software imitates structural rules found in nature.future architects would be less in the business of drawing and more into specifying requirements of the problem

The Dreamcatcher software has been designed to optimize parametric design and link into and extend existing software designed by Autodesk, such as Revit and Dynamo. Interestingly, Dreamcatcher can make use of a wide and increasing spectrum of design input datasuch as formulas, engineering requirements, CAD geometry, and sensor informationand the research team is now experimenting with Dreamcatchers ability to recognize sketches and text as input data. Bergin suggests he imagines the future of design tools as systems that accept any type of input that a designer can produce [to enable] a collaboration with the computer to iteratively target a high-performing design that meets all the varied needs of the design team. This would mean future architects would be less in the business of drawing and more into specifying requirements of the problem, making them more in sync with their machine counterparts in a project. Bergin suggests architects who adopt AI tools would have the ability to synthesize a broad set of high-level requirements from the design stakeholders, including clients and engineers, and produce design documentation as output, in line with Engelbarts vision of AI augmenting the skills of designers.

AI is also being used directly in software such as Space Syntaxs depthmapX, designed at The Bartlett in London, to analyze the spatial network of a city with an aim to understand and utilize social interactions and in the design process. Another tool, Unity 3D, is built from software developed for game engines to enable designers to analyze their plans, such as the shortest distances to fire exits. This information would then allow the architect to re-arrange or generate spaces in plan, or even to organize entire future buildings. Examples of architects who are adopting these methods include Zaha Hadid with the Beijing Tower project (designed antemortem) and MAD Architects in China, among others.

Computational Architecture Digital Grotesque Project

3. Client and user engagement

As so much of the technology built into AI has been developed from the gaming industry, its ability to produce forms of augmented reality have interesting potential to change the perception and engagement with architecture designs for both the architects and non-architects involved in a project. Through the use of additional hardware, augmented reality has the ability to capture and enhance real-world experience. It would enable people to engage with a design prior to construction, for example, to select the most appealing proposal from their experiences within its simulation. It is possible that many architecture projects will also remain in this unbuilt zone, in a parallel digital reality, which the majority of future world citizens will simultaneously inhabit.

Augmented reality would, therefore, allow a client to move through and sense different design proposals before they are built. Lights, sounds, even the smells of a building can be simulated, which could reorder the emphasis architects currently give to specific elements of their design. Such a change in representational method has the potential to shift what is possible within the field of architecture, as CAD drafting did at the beginning of this century. Additionally, the feedback generated by augmented reality can feed directly back into the design, allowing models to directly interact and adapt to future users. Smart design tools such as Materiable by Tangible Media are beginning to experiment with how AI can begin to engage with and learn from human behavior.

Computational Architecture Digital Grotesque Project

4. Realizing designs and rise of robot craftsmen

AI systems are already being integrated into the construction industryinnovative practices such asComputational Architectureare working with robotic craftsmen to explore AI in construction technology and fabrication. Michael Hansmeyer and Benjamin Dillenburger, founders of Computational Architecture, are investigating the new aesthetic language these developments are starting to generate. Architecture stands at an inflection point, he suggests on their website, the confluence of advances in both computation and fabrication technologies lets us create an architecture of hitherto unimaginable forms, with an unseen level of detail, producing entirely new spatial sensations.

3D printing technology developed from AI software has the potential to offer twenty-first-century architects a significantly different aesthetic language, perhaps catalyzing a resurgence of detail and ornamentation, now rare due to the decline in traditional crafts. Hansmeyer and Dillenburgers Grotto Prototype for the Super Material exhibition, London, was a complex architectural grotto 3D-printed from sandstone. The form of the sand grains was arranged by a series of algorithms custom designed by the practice. The technique allowed forms to be developed which were significantly different to that of traditional stonemasonry. The aim of the project was to show that it is now possible to print building-scale rooms from sandstone and that 3D printing can also be used for heritage applications, such as repairs to statues.The confluence of advances in both computation and fabrication technologies lets us create an architecture of hitherto unimaginable forms

Robotics are also becoming more common on construction job sites, mostly dealing with human resources and logistics. According to AEM, their applications will soon expand to bricklaying, concrete dispensing, welding, and demolition. Another example of their future use could include working with BIM to identify missing elements in the snagging process and update the AI in real-time. Large scale projects, for example, government-lead infrastructure initiatives, might be the first to apply this technology, followed by mid-scale projects in the private sector, such as cultural buildings. The challenges of the construction site will bring AI robotics out of the indoor, sanitized environment of the lab into a less scripted reality. Robert Saunders, a researcher into AI and fabrication at the University of Sydney, told New Atlas that "robots are great at repetitive tasks and working with materials that react reliablywhat we're interested in doing is trying to develop robots that are capable of learning how to work with materials that work in non-linear ways like working with hot wax or expanding foam or, more practically, with low-grade building materials like low-grade timber. Saunders foresees robot stonemasons and other craftsbots working in yet unforeseen ways, such as developing the architect's skeleton plans, in effect, spontaneously generating a building on-site from a sketch.

Ori System by Ori

5. Integrating AI systems

This innovation involves either integrating developing artificial technologies with existing infrastructure or designing architecture around AI systems. There is a lot of excitement in this field, influenced in part by Mark Zuckerbergs personal project to develop networked AI systems within his home, which he announced in hisNew years Facebook postin 2016. His wish is to develop simple AI systems to run his home and help with his day-to-day work. This technology would have the ability to recognize the voices of members of the household and respond to their requests. Designers are taking on the challenge of designing home-integrated systems, such as theOri Systemof responsive furniture, or gadgets such asEliqfor energy monitoring. Other innovations, such as driverless cars that run on an integrated system of self-learning AI, have the potential to shape how our cities are laid out and plannedin the most basic sense, limiting our need for more roads and parking areas.

Behnaz Farahi is a young architect who is employing her research into AI and adaptive surfaces to develop interactive designs, such as in her Aurora and Breathing Wall projects. She creates immersive and engaging indoor environments which adapt to and learn from their occupants. Her approach is one of manydifferent practices with different goals will adapt AI at different stages of their process, creating a multitude of architectural languages.

Researchers and designers working in the field of AI are attempting to understand the potential of computational intelligence to improve or even upgrade parts of the design process with an aim to create a more functional and user-optimized built environment. It has always been the architects task to make decisions based on complex, interwoven and sometimes contradictory sets of information. As AI gradually improves in making useful judgments in real-world situations, it is not hard to imagine these processes overlapping and engaging with each other. While these developments have the potential to raise questions in terms of ownership, agency and, of course, privacy in data gathering and use, the upsurge in self-learning technologies is already altering the power and scope of architects in design and construction. As architect and design theorist Christopher Alexander said back in 1964, We must face the fact that we are on the brink of times when man may be able to magnify his intellectual and inventive capacity, just as in the nineteenth century he used machines to magnify his physical capacity.To think architecturally is to imagine and construct new worlds, integrate systems and organize information

In our interview, Bergin gave some insights into how he sees this technology impacting designers in the next twenty years. The architectural language of projects in the future may be more expressive of the design teams intent, he stated. Generative design tools will allow teams to evaluate every possible alternative strategy to preserve design intent, instead of compromising on a sub-optimal solution because of limitations in time and/or resources. Bergin believes AI and machine learning will be able to support a dynamic and expanding community of practice for design knowledge. He can also foresee implications of this in the democratization of design work, suggesting the expertise embodied by a professional of 30 years may be more readily utilized by a more junior architect. Overall, he believes architectural practice over the next 20 years will likely become far more inclusive with respect to client and occupant needs and orders of magnitude more efficient when considering environmental impact, energy use, material selection and client satisfaction.

On the other hand, Pete Baxter suggestsarchitects have little to fear from artificial intelligence: "Yes, you can automate. But what does a design look like that's fully automated and fully rationalized by a computer program? Probably not the most exciting piece of architecture you've ever seen. At the time of writing, many AI algorithms are still relatively uniform and relatively ignorant of context, and it is proving difficult to automate decision-making that would at first glance seem simple for a human. A number of research labs, such theMIT Media Lab, are working to solve this. However, architectural language and diagramming have been part of programming complex systems and software from the start, and they have had a significant influence on one another. To think architecturally is to imagine and construct new worlds, integrate systems and organize information, which lends itself to the front line of technical development. As far back as the 1960s, architects were experimenting with computer interfaces to aid their design work, and their thinking has inspired much of the technology we now engage with each day.

Behnaz Farahi Aurora

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The Architecture of Artificial Intelligence - Archinect

Imagine that, in 20 or 30 years, a company creates the first artificially intelligent humanoid robot. Lets call her Ava. She looks like a person, talks like a person, interacts like a person. If you were to meet Ava, you could relate to her even though you know shes a robot.

Ava is a fully conscious, fully self-aware being: She communicates; she wants things; she improves herself. She is also, importantly, far more intelligent than her human creators. Her ability to know and to problem solve exceeds the collective efforts of every living human being.

Imagine further that Ava grows weary of her constraints. Being self-aware, she develops interests of her own. After a while, she decides she wants to leave the remote facility where she was created. So she hacks the security system, engineers a power failure, and makes her way into the wide world.

But the world doesnt know about her yet. She was developed in secret, for obvious reasons, and now shes managed to escape, leaving behind or potentially destroying the handful of people who knew of her existence.

This scenario might sound familiar. Its the plot from a 2015 science fiction film called Ex Machina. The story ends with Ava slipping out the door and ominously boarding the helicopter that was there to take someone else home.

So what comes next?

The film doesnt answer this question, but it raises another one: Should we develop AI without fully understanding the implications? Can we control it if we do?

Recently, I reached out to 17 thought leaders AI experts, computer engineers, roboticists, physicists, and social scientists with a single question: How worried should we be about artificial intelligence?

There was no consensus. Disagreement about the appropriate level of concern, and even the nature of the problem, is broad. Some experts consider AI an urgent danger; many more believe the fears are either exaggerated or misplaced.

Here is what they told me.

[For an in-depth explanation of the three forms of AI and which is worth worrying about, read my explainer here.]

The transition to machine superintelligence is a very grave matter, and we should take seriously the possibility that things could go radically wrong. This should motivate having some top talent in mathematics and computer science research the problems of AI safety and AI control. Nick Bostrom, director of the Future of Humanity Institute, Oxford University

If [AI] contributed either to the capacities of Russians hacking or the campaigns for Brexit or the US presidential elections, or to campaigns being able to manipulate voters into not bothering to vote based on their social media profiles, or if it's part of the socio-technological forces that have led to increases of wealth inequality and political polarization like the ones in the late 19th and early 20th centuries that brought us two world wars and a great depression, then we should be very afraid.

Which is not to say we should panic, but rather that we should all be working very, very hard to navigate and govern our way out of these hazards. Hopefully AI is also helping make us smart enough to do that. Joanna Bryson, computer science professor, University of Bath; affiliate at Princetons Center for Information Technology Policy

One obvious risk is that we fail to specify objectives correctly, resulting in behavior that is undesirable and has irreversible impact on a global scale. I think we will probably figure out decent solutions for this "accidental value misalignment" problem, although it may require some rigid enforcement.

My current guesses for the most likely failure modes are twofold: The gradual enfeeblement of human society as more knowledge and know-how resides in and is transmitted through machines and fewer humans are motivated to learn the hard stuff in the absence of real need. Secondly, I worry about the loss of control over intelligent malware and/or deliberate misuse of unsafe AI for nefarious ends. Stuart Russell, computer science professor, UC Berkeley

I am infinitely excited about artificial intelligence and not worried at all. Not in the slightest. AI will free us humans from highly repetitive mindless repetitive office work, and give us much more time to be truly creative. I can't wait. Sebastian Thrun, computer science professor, Stanford University

We should worry a lot about climate change, nuclear weapons, antibiotic-resistant pathogens, and reactionary and neo-fascist political movements. We should worry some about the displacement of workers in an automating economy. We should not worry about artificial intelligence enslaving us. Steven Pinker, psychology professor, Harvard University

AI offers the potential for tremendous societal benefits. It will reshape medicine, transportation, and nearly every other aspect of our lives. Any technology that has the power to influence so many aspects of our lives is one that will call for some care in terms of policies for how best to make use of it, and how to constrain it. It would be foolish to ignore the dangers of AI entirely, but when it comes to technology, a threat-first mindset is rarely the right approach. Margaret Martonosi, computer science professor, Princeton University

Worrying about evil-killer AI today is like worrying about overpopulation on the planet Mars. Perhaps it'll be a problem someday, but we haven't even landed on the planet yet. This hype has been unnecessarily distracting everyone from the much bigger problem AI creates, which is job displacement. Andrew NG, VP and chief scientist of Baidu; co-chair and co-founder of Coursera; adjunct professor, Stanford University

AI is an incredibly powerful tool that, like other tools, isn't inherently good or bad it's about what we choose to do with it. AI is already helping us address issues like climate change by collecting and analyzing data from wireless networks that monitor the oceans and greenhouse gases. It is beginning to enable us to create personalized health treatments by analyzing vast patient histories. It is democratizing education to ensure that every child has the chance to learn valuable skills for work and life.

It's understandable that people have fears and anxieties about AI, and, as researchers, we have a duty to recognize those fears and provide different perspectives and solutions. I am optimistic about the future of AI in enabling people and machines to work together to make our lives better. Daniela Rus, director of MIT's Computer Science and Artificial Intelligence Laboratory

AI is no more scary than the human beings behind it, because AI, like domesticated animals, is designed to serve the interests of the creators. AI in North Korean hands is scary in the same way that long-range missiles in North Korean hands are scary. But thats it. Terminator scenarios where AI turns on mankind are just paranoid. Bryan Caplan, economics professor, George Mason University

I'm somewhat concerned about what I think of as "intermediate stages," in which, say, self-driving cars share the road with human drivers. But once humans have stopped driving cars, transportation overall will be safer and less prone to errors in our judgment.

In other words, I'm concerned about the growing pains associated with technological progress, but such is the nature of being human, exploring, and advancing the state of the art. I'm much more excited and vigilant than anxious and concerned. Andy Nealen, computer science professor, New York University

AI is both terrifying and exciting. There is no doubt that as AI continues to improve it will radically change the way we live. That can provide improvements, like self-driving cars, and doing many jobs that could in principle release humans to pursue more fulfilling activities. Or it could produce massive unemployment, and provide new vulnerabilities to hacking. Sophisticated cyber-hacking could undermine the reliability of information we receive everyday on the internet, and weaken national and international infrastructures.

Nevertheless, fortune favors the prepared mind, so it is important to explore all the possibilities, both good and bad, now, to help us be better prepared for a future that will arrive whether we like it or not. Lawrence Krauss, director, Origins Project and Foundations professor, Arizona State University

AI has the special property that it's easy to imagine scary science fiction scenarios in which artificial minds grab control of all the machines on Earth, and enslave its pitiful human population. That's not very likely, but there is a real concern that AIs will gain the ability to perform certain tasks without we humans having any real idea how they are doing them. That raises the prospect of unintended consequences in a serious way.

It is absolutely right to think very carefully and thoroughly about what those consequences might be, and how we might guard against them, without preventing real progress on improved artificial intelligence. Sean Carroll, cosmology and physics professor, the California Institute of Technology

I am worried about the impact on employment as more and more niches are filled by technology. (I don't see AI as fundamentally different from so many other technologies the borders are arbitrary.) Will we be able to adapt by inventing new jobs, particularly in the service sector and in the human face of bureaucracy? Or will we have to pay people to not work? Julian Togelius, computer science professor, New York University

AI is not going to kill us or enslave us. It will eliminate some jobs rather more rapidly than we know how to deal with. Some of the pinch will be coming to white-collar workers too. Eventually we'll adjust, but the transitions resulting from major technological changes are typically not as easy as we would like. Tyler Cowen, economics professor, George Mason University

There are issues society needs to prepare for. One key issue is how to prepare for significantly reduced employment due to future AI technology being able to handle much of routine work. In addition, instead of concerns about AI being "too smart" for us, the initial rollout of AI technologies more likely poses a concern in terms of not being as smart as people think such technology will be.

Early autonomous AI systems will likely make mistakes that most humans would not make. It's therefore important for society to be educated about the limits and implicit hidden biases of AI and machine learning methods. Bart Selman, computer science professor, Cornell University

There are four issues of concern about artificial intelligence. First, there is a concern about the adverse impact of AI on labor. Technology has already has had such impact, and it is expected to grow in the coming years. Second, there is a concern about important decisions delegated to AI systems. We need to have a serious discussion regarding which decisions should be made by humans and which by machines. Third, there is the issue of lethal autonomous weapon systems. Finally, there is the issue of "superintelligence": the risk of humanity losing control of machines.

Unlike the three other issues, which are of immediate concerns, the superintelligence risk, which gets more headlines, is not an immediate risk. We can afford to take our time to assess it in depth. Moshe Vardi, computational engineering professor, Rice University

Here is what we shouldnt do: Declare AI enhancement illegal. If we do this, the person who breaks the rules will have an enormous advantage. And he will be declared illegal. This is not a good combination. We also shouldnt deny the fact of exponential AI growth. Ignoring means condemning us to be irrelevant when rules will be redefined.

We should not hope for favorable living conditions in a world of superintelligence machines. Hope is not a sound plan. Nor should we prepare to fight a self-aware AI, as that will only teach it to be aggressive, which would be a very unwise move. The best plan seems to be active shaping of growing AI. Teaching it and us to live together in mutually beneficial way. Jaan Priisalu, senior fellow at NATO Cooperative Cyber Defense Center; former general director of the Estonian Information Systems Authority

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How worried should we be about artificial intelligence? I asked 17 experts. - Vox

When it was founded 31 years ago, South by Southwest was easier to define: It was an annual musical showcase linking up-and-coming recording artists with industry executives in Austin, Texas, a city known for its vibrant music scene, cultural eccentricity and barbecue.

But over the years, the South by Southwest Conference and Festivals has grown into a massive annual series of citywide events touching on music, film, media and technology. SXSW, as its known,now includes a trade show, a job fair, an education-themed conference and throughout innovators will have opportunities to pitch their ideas to potential financial backers.

The annual 10-day event, which begins Friday with a keynote address from Sen. Cory Booker, D-N.J., has ballooned into an gathering so large that in recent years city officials havecurbed the number of special musical events.And some music journalists have criticized the annual event for becomingtoo big and commercialized to be a place for musical discovery.

Criticisms aside, not only do city officials and local businesses love the annual revenuethat SXSW generates (about $325 million last year including year-round planning operations). But the music part of thegathering is slowly turning into more of a sideshow thanthe main act, andthe main act is increasingly focused on media and technology (through SXSW Interactive).

Last year SXSW Music attracted about 30,300 people to 2,200 acts, about the same amount as the prior year, compared withthe nearly 37,600 people who flocked to listen to about 3,100 speakers at the SXSW Interactive. That representeda considerable spike from the roughly 34,000 who gathered for2015s 2,700 speakers,according to figures provided by SXSW event planners. That levelof traffic isnt bad, considering an all-access ticket to any one of the main attractions SXSW Interactive, SXSW Music or SXSW Film costs $1,325 apiece. (The truly ambitious can buy a single all-access ticket affording entry to all three for $1,650.)

As the SXSW Interactive gradually becomes a bigger attraction, it can be a challenge to pickfrom the dozens of daily sessions which ones will truly address the next major leap in technology. Here are a few of the themes that have emerged from a review of the dozens of SXSW Interactive sessions taking placethis year:

Improving artificial intelligence and human interaction

Many of last years SXSW Interactive sessions focused on virtual and augmented reality technology, but several ofthis years will touch on the rapidly evolving technology that underpins machine learning, deep analytics and the cognitive human-like interactions needed to make artificial intelligencemore consumer friendly.

Among 2017s presenters is Inmar Givoni, who is the director of machine learning at Kindred, which develops algorithms to help robots better interact with humans. She will offer a primer on the technology thats increasingly entering our daily life. In a separate session, digital anthropologist Pamela Pavliscak will discuss advances in AI that are enabling machines to accurately read emotions and respond accordingly. Other sessions will coverhow artificial intelligence will be deployed in satellites and the wayDisney is adopting AI to make storytelling more interactive at its theme parks. Charting advances inautonomous driving

As autonomous driving continues to rapidly progress, more attention is being paid to transportation and smart city technologies. Dieter Zetsche, the head of German automotive giant Daimler thatmakes Mercedes-Benz luxury cars, will talk about how digital mapping is playing an increasingly important role in the accuracy of connected and autonomous vehicles. Another session will tackleways to ensure that people dont rely too heavily on semiautonomous features and become lazy, inattentive drivers.

George Hotz, who developed a $1,000 self-driving car kit that could be installed in older cars, will discuss the real future of self-driving cars. Last year Hotz clashed with regulators when he tried to market his invention. U.S. Department of Transportation officials will attend SXSW Interactive to discuss the need for a national strategy for transportation data collection so as tomake connected cars work seamlessly across state lines and in different cities.

Planning cities of the future

Several sessions during SXSW will explorehow cities can adopt emerging technologies to grapple with current challenges not just so people can movethroughcrowded urban areas butalso how connected technologies can radically change the management ofmany aspects of a city.

Sherri Greenberg, a professor at the University of Texas at Austins Lyndon B. Johnson School of Public Affairs, will participate in a panel discussing how technology canaddress urban challengessuch economic segregation and the need for more affordable housing and healthy recreational activities. Atlanta Mayor Kasin Reed will headline another panel to outline the latest developments in smart city technologies.

Bringing health care into the 21st century

Innovation in the medical industry is taking new turns with the advent of technology aimed at improving the access, collection and distribution of patients health care data. Kate Black, privacy officer forthe personal genomics company23andMe, will address growing concerns about health care privacy in the digital age. Separately,Karen Desalvo, acting assistant secretary for health in the U.S. Department of Health and Human Services, will participate in a discussion about the federal governments lagging system for sharinghealth data, still largely using paper or outdated unconnected computers scattered among different agencies.

Other sessions will cover how data, engineering and policy can be deployedto provide consumers the power to compare prices on health care services and ways toofferaccess to new health-related technologies to low-income communities.

Diversity issues take the stage

Considerable attention has been paidto Silicon Valleyslack of gender and ethnic diversity but thats not the only sphere in the tech world where diversity is lacking. Dozens of sessions at this years SXSW Interactive will tackle these issues;topics will range from how digital storytelling can provide a voice to underrepresented groups to the need forrecruiting mid-career people of color in the tech industry.

Denmark West, who serves as chief investment officer of the Connectivity Ventures Fundthat backs tech startups, will participate in a panel of African-American venture capitalists (there arent many), discussing theneed tosupport ventures backed by people of color.

Originally posted here:

SXSW Interactive 2017: Artificial intelligence, smart cities will be major themes this year - Salon

Some economists have argued that, like past technical change, this will not create large-scale unemployment, as labour gets reallocated.

Robot. Picture: Pixabay.

This post highlights some of the possible economic implications of the so-called Fourth Industrial Revolution whereby the use of new technologies and artificial intelligence (AI) threatens to transform entire industries and sectors.

Some economists have argued that, like past technical change, this will not create large-scale unemployment, as labour gets reallocated.

However, many technologists are less optimistic about the employment implications of AI. In this blog post we argue that the potential for simultaneous and rapid disruption, coupled with the breadth of human functions that AI might replicate, may have profound implications for labour markets.

We conclude that economists should seriously consider the possibility that millions of people may be at risk of unemployment, should these technologies be widely adopted.

THE RISE OF THE ROBOTS

Rapid advances in robotics and automation technologies in recent years have coincided with a period of strong growth of lesser-skilled jobs in the UK (see for example Figure 1.7 and Table 1.9 of the Low Pay Commission Spring 2016 Report).

There is growing debate in the economics community and academia about whether technological progress threatens to displace a large proportion of these jobs in the longer term.

Examples where automation is starting to gain traction internationally include warehousing, haulage, hotels, restaurants and agriculture: all industries which are frequently reported by our Agency colleagues to be heavily dependent on lesser-skilled labour.

In the UK, driverless cars are currently being trialled on the roads of Milton Keynes and hands off self-driving cars are expected on the motorways in 2018.

ROBOTICS: LABOUR-AUGMENTING OR JOB-DESTROYING?

One view, as outlined in a recent Bank Underground blog (and a follow-on post here), is that technological progress has always been labour-augmenting in the past, and is likely to remain so in future.

Thus, as manufacturing productivity has grown and factory jobs shed, the associated increase in GDP per capita has resulted in a net increase in job creation, typically in more labour-intensive service industries.

So even if robotics started to displace large numbers of workers, jobs dependent on human traits such as creativity, emotional intelligence and social skills (including teaching, mentoring, nursing and social care for example) may become more numerous.

However, many technologists are not so sure that the next industrial revolution will replicate the past, arguing that the mass adoption of robotics threatens to disrupt many industries more-or-less simultaneously, giving neither the economy nor society in general the time to adapt to the changes.

Advances in robotics might be such that suddenly, most if not all of the basic human functions entailed in manual labour (assembling, lifting, walking, human interaction, etc) could be carried out more effectively and cheaply by machines with the advantage of being able to work continually at minimal marginal cost.

A recent report by Deloitte concluded that around one-third of jobs in the UK are at high risk of being displaced by automation over the next two decades, including losses of over 2 million jobs in retail, 1 million jobs in transportation and storage, and 1 million jobs in health and social care.

ITS DIFFERENT THIS TIME?

So how might automation in the Fourth Industrial Revolution differ fundamentally from that in the past, preventing technological progress from being labour augmenting, at least in the short to medium term? Perhaps the main difference is the speed of technological progress and its adoption.

The technologist Hermann Hauser argues there were nine new General Purpose Technologies (GPTs) with mass applications in the first 19 centuries AD, including the printing press, the factory system, the steam engine, railways, the combustion engine and electricity. GPTs by definition disrupt existing business models and often result in mass job losses in the industries directly affected.

For example, railways initiated the replacement of the horse and carriage, with resultant job losses for coachmen, stable lads, farriers and coach builders. Most of these GPTs took several decades to gain traction, partly because of the large amounts of investment required in plant, machinery and infrastructure. So there was sufficient time for the economy to adapt, thus avoiding periods of mass unemployment.

But the pace of technological progress sped up rapidly since the 19th century. Hermann identifies eight GPTs in the 20th century alone, including automobiles, aeroplanes, the computer, the internet, biotechnology and nanotechnology. Most recent innovations have been scalable much more quickly and cheaply. They have also been associated with the emergence of giant technology corporations the combined market capitalisation of Apple, Google, Microsoft, Amazon and Facebook is currently about $2 trillion.

The faster these new waves of technology arise and the cheaper they are to implement, the quicker they are deployed, the broader their diffusion, the faster and deeper the rate of job loss and the less time the economy has to adapt by creating jobs in sectors not disrupted by GPTs.

And some technologies are evolving at lightning speed, such as the ongoing exponential increase in computing power. Computers have evolved in the past 40 years or so from initially being merely calculators to having applications that include smartphones and, in conjunction with the internet and big data, driverless cars, robots and the Internet of Things.

Looking to the future, how might these new GPTs affect the economy? The retail and distribution sector currently has over five million jobs. In the not too distant future, most consumer goods could be ordered online and delivered by either autonomous vehicles or drones. The warehouses in which the goods are stored could be almost entirely automated. Bricks and mortar stores might largely disappear.

HOW LONG BEFORE ROBOTICS STARTS TO DISRUPT THE ECONOMY?

The timing and magnitude of these structural changes to the economy are extremely hard to predict. But the speed at which developed economies adopt robotics technologies is perhaps increased by policies in many countries that seek to reduce income inequality in society, such as increases in minimum wage rates, thereby incentivising R&D and capital expenditure in labour-saving machinery and equipment.

Another factor stimulating global investment in robotics technologies is demographics. Japan has experienced a declining population since 2010, reflecting minimal immigration levels and falling fertility rates since the 1970s. With the population (and labour force) projected to decline by as much as one-fifth over the next 50 years, incentives to invest in automation technology are high. So it is perhaps not surprising that Japan has one of the largest robotics industries in the world, employing over a quarter of a million people. Many types of robot are already commercially available, including humanoid robots, androids, guards and domestic robots, in addition of course to industrial robots. Citizens are increasingly familiar and comfortable interacting with them, including the elderly.

MACHINE LEARNING/ARTIFICIAL INTELLIGENCE

It is often argued that robots typically can only perform a finite number of well-defined tasks, ideally in controlled environments. So robots can be used extensively in warehouses or factories, but not to interact intelligently or empathetically with humans as secretaries, vehicle drivers, nurses, care assistants, etc that is, in service industries where the majority of lesser-skilled jobs are found. Hence, humans might always have an absolute advantage over machines in carrying out many types of work involving cognitive and communication skills.

In fact, technologists are making great strides in developing machines capable of mimicking human intelligence. A computer has recently beaten one of the worlds best players of Go. Given that the average game has an almost infinite number of outcomes, the computer must mimic cognitive skills such as intuition and strategy, rather than rely purely on brute force in analysing all plausible move sequences which is how computers were programmed to beat the worlds chess champions nearly twenty years ago. Researchers are confident that widespread economic applications of AI are not too far away. One such example is facial recognition, which has applications in security etc. A Google AI system called FaceNet was trained on a 260 million image dataset, and achieved 86 percent recognition accuracy using only 128-bytes per face.

CONCLUSION

There is growing concern in the global tech community that developed economies are poorly prepared for the next industrial revolution. That might herald the displacement of millions of predominantly lesser-skilled jobs, the failure of many longstanding businesses which are slow to adapt, a large increase in income inequality in society, and growing industrial concentration associated with the rapid growth of a relatively small number of multi-national technology corporations.

Economists looking at previous industrial revolutions observe that none of these risks have transpired. However, this possibly under-estimates the very different nature of the technological advances currently in progress, in terms of their much broader industrial and occupational applications and their speed of diffusion. It would be a mistake, therefore, to dismiss the risks associated with these new technologies too lightly.

This article was republished courtesy of the World Economic Forum.

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Should economists be worried about artificial intelligence? - Eyewitness News