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That was illustrated in the fields of genomics, cancer biology, the study of diet, the environment and climate, in risk and regulation, neuroimaging, confidentiality and privacy, and autism research.

But also, it seemed to me that inclusion in the program was a sign of being a non-traditional application area, one more likely to capture the imagination of the media representatives present and the funding agencies that will read the report about the workshop.

We have to steer a path between the Scylla of complacency and sclerosis, of resting on our laurels, of reluctance to change, and the Charybdis of frantic change, of forgetting where we’ve come from and where we are going, of always trying to wear the latest fashion.

see no evidence that the view of data science being promoted by its enthusiasts has any prospect of replacing our discipline in the diverse areas in which it has become central, many of which were named above.

think we have a great tradition and a great future, both far longer than the concentration span of funding agencies, university faculties, and foundations—people who play zero-sum funding games across disciplines.

We might miss out on the millions being lavished on data science right now, but that’s no reason for us to stop trying to do the best we can at what we do best, something that is far wider and deeper than data science.

In the year 2013, we celebrated the 300th anniversary of Bernoulli’s Ars conjectandi, the 250th anniversary of Bayes’ Essay, the 200th anniversary of Laplace’s Essai philosophique, the 150th anniversary of Galton’s mapping the weather, the 101st anniversary of Fisher’s clarion call for maximum likelihood, and the 51st anniversary of Tukey’s The Future of Data Analysis.

Perhaps the last trilobite thought to herself at the end of the Palaeozoic age, “I tried to evolve, but things were changing too fast for me.” But trilobites lasted for 300 million years and were on every continent on earth.

Predictive Policing: The Future of Law Enforcement?

For years, businesses have used data analysis to anticipate market conditions or industry trends and drive sales strategies.

and some in the field believe it has the potential to transform law enforcement by enabling police to anticipate and prevent crime instead of simply responding to it.

Researchers, law enforcement officers, crime analysts and scientists gathered in Los Angeles for three days to explore the policy implications, privacy issues and technology of predictive policing.

Predictive policing, in essence, is taking data from disparate sources, analyzing them and then using the results to anticipate, prevent and respond more effectively to future crime.

"The predictive vision moves law enforcement from focusing on what happened to focusing on what will happen and how to effectively deploy resources in front of crime, thereby changing outcomes,"

writes Charlie Beck, chief of the Los Angeles Police Department.[1] Beck told participants that perhaps the greatest benefit to predictive policing is the discovery of new or previously unknown patterns and trends.

Just as Walmart found increased demand for strawberry Pop-Tarts preceding major weather events, LAPD has found its own subtle patterns when examining data that have helped the department accurately anticipate and prevent crime.

Instead, it borrows from the principles of problem-oriented policing, community policing, evidence-based policing, intelligence-led policing and other proven policing models.

George Gascón, chief of police for the San Francisco Police Department, noted that predictive policing is the perfect tool to help departments become more efficient as budgets continue to be reduced.

"With predictive policing, we have the tools to put cops at the right place at the right time or bring other services to impact crime, and we can do so with less,"

Current analytic tools and techniques like hot spots, data mining, crime mapping, geospatial prediction and social network analysis can be applied to a broad range of criminal justice problems.

For instance, they can be used to anticipate localized crime spikes, inform city and neighborhood planning and aid in police management decisions.

Police began looking at data gathered over the years, and based on that information, they were able to anticipate the time, location and nature of future incidents.

The Arlington, Texas, Police Department used data on residential burglaries to identify hot spots and then compared these locations to areas with code violations.

We should engage privacy advocates and community leaders from the outset to explain the program and get their ideas and input to alleviate their concerns."

instead, they anticipate particular times and locations where crime is likely to occur.[2] Yet privacy and civil liberty issues are critically interrelated with predictive policing and must be addressed.

"We have a solemn obligation and a strategic imperative for the success of predictive policing to put privacy, civil rights and civil liberties in the forefront from the outset,"

Participants stressed the importance of setting up a thorough privacy policy, training personnel to use it properly, enforcing accountability and continually refining the policy.

Along with watching quality, police departments also need to tap into the wealth of nontraditional data available locally, such as medical and code-compliance data.

"Part of the challenge is understanding what all the available data are and then finding a way to fuse that data, bring the people who use that data together, and approach it from a holistic perspective,"

Books & Resources

In Oil Spill—The Rest of the Story (grades 6–12), for example, students build a watershed model to explore surface runoff, play Water-Quality Limbo to demonstrate their understanding of management practices to keep water clean, and brainstorm ways for the community to limit or prevent nonpoint-source water pollution in the estuaries.

and describe and compare salinity graphs.The site’s System-wide Monitoring Program (SWMP, pronounced “swamp”) Graphing Tool enables middle and high school students to work with authentic weather and water-quality data from NOAA to learn more about estuaries.

AI, Robotics, and the Future of Jobs

The vast majority of respondents to the 2014 Future of the Internet canvassing anticipate that robotics and artificial intelligence will permeate wide segments of daily life by 2025, with huge implications for a range of industries such as health care, transport and logistics, customer service, and home maintenance.

There will be greater differentiation between what AI does and what humans do, but also much more realization that AI will not be able to engage the critical tasks that humans do.” Another group of experts feels that the impact on employment is likely to be minimal for the simple reason that 10 years is too short a timeframe for automation to move substantially beyond the factory floor.

But there are only 12 years to 2025, some of these technologies will take a long time to deploy in significant scale… We’ve been living a relatively slow but certain progress in these fields from the 1960s.” Christopher Wilkinson, a retired European Union official, board member for, and Internet Society leader said, “The vast majority of the population will be untouched by these technologies for the foreseeable future.

Glenn Edens, a director of research in networking, security, and distributed systems within the Computer Science Laboratory at PARC, a Xerox Company, wrote, “There are significant technical and policy issues yet to resolve, however there is a relentless march on the part of commercial interests (businesses) to increase productivity so if the technical advances are reliable and have a positive ROI then there is a risk that workers will be displaced.

The race between automation and human work is won by automation, and as long as we need fiat currency to pay the rent/mortgage, humans will fall out of the system in droves as this shift takes place…The safe zones are services that require local human effort (gardening, painting, babysitting), distant human effort (editing, coaching, coordinating), and high-level thinking/relationship building.

The situation is exacerbated by total failure of the economics community to address to any serious degree sustainability issues that are destroying the modern ‘consumerist’ model and undermining the early 20th century notion of ‘a fair day’s pay for a fair day’s work.’ There is great pain down the road for everyone as new realities are addressed.

The short answer is that if the job is one where that question cannot be answered positively, that job is not likely to exist.” Tom Standage, digital editor for The Economist, makes the point that the next wave of technology is likely to have a more profound impact than those that came before it: “Previous technological revolutions happened much more slowly, so people had longer to retrain, and [also] moved people from one kind of unskilled work to another.

I’m reminded of the line from Henry Ford, who understood he does no good to his business if his own people can’t afford to buy the car.” Alex Howard, a writer and editor based in Washington, D.C., said, “I expect that automation and AI will have had a substantial impact on white-collar jobs, particularly back-office functions in clinics, in law firms, like medical secretaries, transcriptionists, or paralegals.

And education systems in the U.S. and much of the rest of the world are still sitting students in rows and columns, teaching them to keep quiet and memorize what is told to them, preparing them for life in a 20th century factory.” Bryan Alexander, technology consultant, futurist, and senior fellow at the National Institute for Technology in Liberal Education, wrote, “The education system is not well positioned to transform itself to help shape graduates who can ‘race against the machines.’ Not in time, and not at scale.

Think outside the job.” Bob Frankston, an Internet pioneer and technology innovator whose work helped allow people to have control of the networking (internet) within their homes, wrote, “We’ll need to evolve the concept of a job as a means of wealth distribution as we did in response to the invention of the sewing machine displacing seamstressing as welfare.” Jim Hendler, an architect of the evolution of the World Wide Web and professor of computer science at Rensselaer Polytechnic Institute, wrote, “The notion of work as a necessity for life cannot be sustained if the great bulk of manufacturing and such moves to machines—but humans will adapt by finding new models of payment as they did in the industrial revolution (after much upheaval).” Tim Bray, an active participant in the IETF and technology industry veteran, wrote, “It seems inevitable to me that the proportion of the population that needs to engage in traditional full-time employment, in order to keep us fed, supplied, healthy, and safe, will decrease.

Kevin Carson, a senior fellow at the Center for a Stateless Society and contributor to the P2P Foundation blog, wrote, “I believe the concept of ‘jobs’ and ‘employment’ will be far less meaningful, because the main direction of technological advance is toward cheap production tools (e.g., desktop information processing tools or open-source CNC garage machine tools) that undermine the material basis of the wage system.

The real change will not be the stereotypical model of ‘technological unemployment,’ with robots displacing workers in the factories, but increased employment in small shops, increased project-based work on the construction industry model, and increased provisioning in the informal and household economies and production for gift, sharing, and barter.” Tony Siesfeld, director of the Monitor Institute, wrote, “I anticipate that there will be a backlash and we’ll see a continued growth of artisanal products and small-scale [efforts], done myself or with a small group of others, that reject robotics and digital technology.” A

In the long run this trend will actually push toward the re-localization and re-humanization of the economy, with the 19th- and 20th-century economies of scale exploited where they make sense (cheap, identical, disposable goods), and human-oriented techniques (both older and newer) increasingly accounting for goods and services that are valuable, customized, or long-lasting.” In the end, a number of these experts took pains to note that none of these potential outcomes—from the most utopian to most dystopian—are etched in stone.

rather it’s a political choice.” Jason Pontin, editor in chief and publisher of the MIT Technology Review, responded, “There’s no economic law that says the jobs eliminated by new technologies will inevitably be replaced by new jobs in new markets… All of this is manageable by states and economies: but it will require wrestling with ideologically fraught solutions, such as a guaranteed minimum income, and a broadening of our social sense of what is valuable work.”

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