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Updates from the Center for Data Innovation
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Featured Articles
Survey: Few Americans Willing to Pay for Privacy
Few surveys of Internet users’ attitudes toward online privacy ask about tradeoffs, so the Center for Data Innovation probed Americans’ reactions to a series of likely consequences of reducing online data collection. The survey found that when potential tradeoffs were not part of the question approximately 80 percent of Americans agreed that they would like online services such as Facebook and Google to collect less of their data. But that support eroded when respondents considered these tradeoffs. For example, support dropped by 27 percentage points when respondents considered whether they would like less data collection even if it means seeing more ads than before. And it dropped by 26 percentage points when respondents were asked whether they would like less data collection even if it means losing access to some features they use now. The largest drop in support (53 percentage points) came when respondents were asked whether they would like online services to collect less of their data even if it means paying a monthly subscription fee.
OPEN Government Data Act Signed into Law; Establishes U.S. as Leader in Open Data
The Center for Data Innovation applauded President Trump for signing into law the Open, Public, Electronic, and Necessary (OPEN) Government Data Act, included as Title II of the Foundations for Evidence-Based Policymaking Act (H.R. 4174). The OPEN Government Data Act is a major bipartisan victory for open data. It is now the law of the land that government data should be freely available and accessible to everyone by default. The Center for Data Innovation has long called for comprehensive federal legislation to define the publication of open data as a permanent responsibility of the U.S. government. The OPEN Government Data Act will ensure that the federal government releases valuable data sets, follows best practices in data management, and commits to making data available to the public in a non-proprietary and electronic format.
5Q’s for Baher Al Hakim, CEO of Medicus AI
The Center for Data Innovation spoke with Baher Al Hakim, chief executive officer and founder of Medicus AI, an AI-based health platform based in Vienna. Dr. Al Hakim discussed how such products are transforming the healthcare sector, simplifying the relations between healthcare providers and patients, and leading to better health outcomes.
Events
The Impact of AI on Diplomacy and International Relations
There have been significant advances in AI over the past decade which have lead to many debates about its potential social, economic, and security impact. However, little sustained attention has been paid to the impact of AI on international relations in general, and on the work of diplomats and policy makers in particular. Join DiploFoundation and the Center for Data Innovation on Monday, January 28, in Brussels, to discuss the need for further research, capacity development, and practice in the sphere of AI and international relations with other stakeholders from government, the private sector, and civil society.
What’s Next for Open Data in the United States?
On January 14, 2019, President Trump signed the OPEN Government Data Act (H.R. 4174). This law is a major milestone for open data, as it will require the federal government to make government data available to the public in a non-proprietary and machine-readable format by default. Now that the law has been enacted, what should Congress and the administration do next to ensure the benefits of open data are fully realized? Join the Center for Data Innovation, BSA | The Software Alliance, the Internet Association, SPARC, the Bipartisan Policy Center, the Data Coalition, and the American Library Association on Thursday, February 7, 2019, in Washington, D.C., for a panel discussion about the future of open data in the United States, including how to address challenges related to implementing the OPEN Government Data Act and opportunities to leverage open data for economic and social benefits.
Using AI to Fight Disinformation in European Elections
As the EU readies for its upcoming elections, accelerating the fight against fake news has become a top priority. Many policymakers are concerned about attempts to covertly use online platforms to insert propaganda and incendiary messages into public discourse by targeting particular groups with disinformation campaigns. One powerful tool in the fight against fake news is AI, which can be used to automatically detect and respond to this content as well as empower users with the ability to verify the veracity of claims. Join the Center for Data Innovation on Wednesday, February 20, in Brussels, for a conversation about how the public and private sectors can work together to accelerate the use of AI to combat fake news.
Weekly News
1. Fitbit Users Can Share Data to Advance Precision Medicine
The U.S. National Institutes of Health (NIH) and Fitbit have launched the Fitbit bring-your-own-device initiative, which allows Fitbit users to share their data with NIH to advance scientific research in precision medicine. Fitbit users can sync their accounts to share data on health indicators such as their physical activity, heart rate, and food and water intake. Participants can also share their electronic health records and answer surveys to provide more health information. The initiative is the first project of NIH’s All of Us Research Program, which aims to improve human health by studying the effects of differences in lifestyle, environment, and genetics.
2. Finland Wants to Teach its Citizens AI
Finland has set a goal of teaching the basics of AI to one percent of its population—55,000 people—to raise awareness about the technology and to equip voters with the knowledge to be active participants in AI public policy debates. The initiative, which originally began as a free-access university course, teaches citizens about AI through an introductory online course. The course, which over 6,000 Finnish citizens had completed by December, includes chapters on machine learning and neural networks.
3. Meet Marty, Giant’s In-Store AI Robot
Giant, a grocery store chain, is implementing an autonomous robotic assistant named Marty in 172 of its stores. Marty uses computer vision to find spills, debris, and other potential hazards, which the robot reports to store employees. Marty also alerts nearby customers, saying “caution, hazard detected.” In addition, Marty scans shelves to find items that are out-of-stock and to find prices that do not match the store’s scanning system.
4. AI Helps Track Influenza Activity
Researchers from Boston Children’s Hospital have developed a method that uses machine learning to accurately estimate influenza activity at the state level in the United States. The method, which uses data from Google searches, electronic health records, and historical flu trends, including spatio-temporal data, provides influenza forecasts a week before traditional reports. The more timely data can help mitigate potential flu outbreaks.
5. Nvidia Turns a Kitchen into a Robotics Lab
Nvidia has created a new kitchen lab, based on an Ikea kitchen, in Seattle to develop robots that can better work alongside humans. For example, one robotic arm inside the lab is learning how to place jars, bottles, and boxes into drawers. The tasks the robots perform will get progressively harder, and Nvidia is also experimenting with teaching the robots basic laws of the physical world, such as gravity, to help the AI systems controlling the robots advance.
6. AI Can Predict The Location of Future Tennis Shots
Researchers from Queensland University of Technology in Australia have developed an AI system that can predict the location of the next tennis shot within one meter. The researchers trained the system on ball behavior, such as the ball’s speed and trajectory, and player behavior, such as foot placement, from 8,780 shots from Rafael Nadal, Roger Federer, and Novak Djokovic using a generative adversarial network. The system predicted the future shot placement of these three players within 0.87 meters, 0.79 meters, and 1.14 meters, respectively.
7. Farming is Becoming Increasingly Data-Oriented
Farmers are increasingly using data to improve their methods. For example, Rivendale Farms in Pennsylvania places collars on 150 cows to monitor their movement and eating patterns. The farm is also using sensors to control the temperature, humidity, and sunlight in a greenhouse. Lastly, the farm has collaborated with Carnegie Mellon University to develop “scouting robots” that will use computer vision to identify which plants are healthy and which are diseased.
8. Detecting Breast Cancer with AI
The UK’s National Health Service (NHS) is launching a trial to learn if AI can diagnose breast cancer. In the trial, Kheiron Medical, a firm that uses AI to detect cancer, is testing its algorithms on tens of thousands of historic mammograms. Kheiron trained it system on a half a million scans from hospitals in Hungary and could help the UK solve its shortage of human radiologists.
9. Detroit is Using AI to Prioritize Roadwork
Detroit is working with startup RoadBotics to use machine learning and driver-collected data to determine which streets needs roadwork. During the pilot, Roadbotics will have drivers travel throughout the city with smartphones mounted in their car to record a continuous stream of video while linking the video to GPS data. Then, to provide a rating of which roads are in need of the most immediate work, RoadBotics will analyze the footage using AI to automatically identify road defects such as potholes and cracks.
10. Using AI to Identify Malnourished Children
German private aid organization Welthungerhilfe is using AI to identify children in India who are suffering from malnutrition, which can be difficult for the human eye to accurately detect. The organization is deploying over 1,000 trained health workers, and the workers will use smartphones to take 3D scans of 10,000 children to determine their height, body volume, and weight ratio. Welthungerhilfe then uses nutritionists and AI from Microsoft’s Azure cloud to analyze the health of the child and provide children with vitamin-rich provisions when necessary.
Data Visualization of the Week
Visualizing How Delhi’s Air Quality Becomes Hazardous in the Winter
 Reuters has created several data visualizations illustrating how Delhi’s air quality declines in the winter as temperatures and wind speed decrease. Hazardous air particles such as dust, dirt, and smoke remain closer to the ground in the colder weather and lower wind speeds trap the pollutants in Delhi. Crop burnings, which are a common practice in Delhi because they are an inexpensive way to prepare an area for new crops, exacerbate the pollution. The visualizations show that one monitoring station only recorded two hourly readings of “good” or “moderate” air quality during the months of October and November, while all other readings at the station ranged from “unhealthy for sensitive groups” to “hazardous.”
Data Set of the Week
Building a More Precise Image Dataset
Chinese technology company Tencent has released Tencent ML-Images, a dataset containing 18 million images across 11,000 categories. The dataset combines images from previously released datasets, removing images labeled in abstract categories like “event” or “summer” and placing other images into more fine grained categories, such as separating images of dogs into categories based on breed. On average, there are nearly 1,450 images per category. In addition, Tencent ML-Images has an average of eight labels per image—many image datasets contain images with only a single label, which can waste useful visual information to train models on because a single label often cannot describe all important objects in an image.
Job Postings
Google Policy Fellow (Paid, Summer 2019)
The Center for Data Innovation is accepting applications for the Google Policy Fellowship program for 2019. The ideal applicant should have a demonstrated interest in the intersection of public policy, technology, and data, as well as exceptional writing abilities. Graduate and undergraduate students are both welcome to apply. Fellows will receive a stipend of $7,500, and the deadline to apply is Friday, February 15th.
Suggestions, comments or tips? Email us at info@datainnovation.org or send us a tweet at @datainnovation. |
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