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Crime Analysts: Using Data to Make Communities Safer

/our-media/indepth/2023/09/crime-analysts-as-profession

Crime analysts identify patterns, trends, and connections in vast datasets to help law enforcement. The crime analysis profession expands along with police data.

justice or data analytics, a Master of Science in law enforcement administration, or a Master of Science in criminal justice. As crime analysis has grown in popularity over the years, colleges ... Crime Analysts as Profession Crime analysts identify patterns, trends, and connections in vast datasets to help law enforcement. The crime analysis profession expands along with police data. /images/InDepth/2023/09/Crime-Analysis-Map.jpg Crime Analysts: Using Data to Make Communities Safer Crime analysis education, certification, careers with police Alisa Leduc Alisa Leduc is a research analyst

Delivery Drones are Coming. Are We Ready?

/our-media/indepth/2023/09/delivery-drones-are-coming

Controlling the airspace for small package delivery by drones or UAS requires planning that is informed by analysis and modeling with tools such as CNA’s UCATS™.

Yang is a systems engineer in CNA’s Center for Data Management Analytics supporting the future integration of emerging technologies, such as UAS and artificial intelligence, for the FAA. Adam ... clients. Mark Lesko is a research scientist in CNA’s Center for Data Management Analytics specializing in issues and analysis related to traditional air traffic management. Controlling

ai with ai: Elfnark’s Lottery Ticket

/our-media/podcasts/ai-with-ai/season-2/2-29

Andy and Dave take a look at the reintroduction of the "AI in Government Act," a bill that intends to get more AI technical experts into the US Government. San Francisco bans facial recognition software (but leaves the door open in the future), while Moscow announces plans to weave AI facial recognition into its urban surveillance net. Facebook opens up its data to academic researchers for analysis. DARPA announces the Air Combat Evolution (ACE) program, to automate air-to-air combat; DARPA also announces Teaching AI to Leverage Overlooked Residuals (TAILOR), to make soldiers fitter, happier, and more productive. And IARPA announces Trojans in AI (TrojAI), an effort to inspect AI for malicious code. In research, Andy and Dave discuss research from Frankle at MIT that proposes a "Lottery Ticket" hypothesis, which suggests only certain "winning combinations" are necessary for training neural networks, and that researchers have been training neural networks that are much larger than they need to be to increase the chances of includes one of these winning combinations. Leon Bottou at Facebook AI proposes a method for using AI to identify causal relationships in data (and which goes against the common modern practice of combining data sets into one giant dataset). And research from Cambridge, George IT, and the University of Pennsylvania demonstrates that Magic: the Gathering is officially the world’s most complicated game (and is Turing complete). In reports of the week, the Stockholm International Peace Research Institute releases the Impact of AI on Strategic Stability and Nuclear Risk. IKV and Pax Christi release The State of AI. Analytics Vedhya has compiled a list of 25 open datasets for deep learning. Benedek Rozemberczki has curated a list of decision tree research papers. The IEEE Spectrum releases a report on Accelerating Autonomous Vehicle Technology. The May 2019 issue of The Scientist contains 15 articles on how Biology is tackling AI. David Kriesel provides A Brief Introduction to Neural Networks. COL Jasper Jeffers wins the 2019 Sci-Fi Writing Contest with AN41. The ICLR 2019 provides video on four talks, including Frankle’s Lottery Ticket hypothesis, and Bottou’s Casual Invariance. Melanie Mitchell gives a Ted Talk on the Collapse of AI and the possibility of an AI winter. And the National Academies-Royal Society Public Symposium will be meeting in DC on 24 May for an International Dialogue on AI.

recognition software (but leaves the door open in the future), while Moscow announces plans to weave AI facial recognition into its urban surveillance net. Facebook opens up its data to academic researchers ... than they need to be to increase the chances of includes one of these winning combinations. Leon Bottou at Facebook AI proposes a method for using AI to identify causal relationships in data (and which goes against the common modern practice of combining data sets into one giant dataset). And research from Cambridge, George IT, and the University of Pennsylvania demonstrates that Magic

John Crissman on an AI Tool for First Responders

/our-media/indepth/2024/10/meet-the-innovator-john-crissman-on-an-ai-tool-for-first-responders

CNA computer scientist John Crissman and his team developed a creative tool using machine learning and AI to improve situational awareness for disaster response.

the Innovator John Crissman is a Research Scientist with CNA’s Center for Data Management and Analytics . He is an expert in artificial intelligence, machine learning, and natural language processing ... artificial intelligence to process sensor data from a natural disaster. What was innovative about your solution? Crissman: This entire challenge was innovative. For the final competition, we were ... , huge fires—and they have lots of sensors. We were in the command center, with each team in its corner, and they sent the teams unidentified streams of data from the sensors, from the Internet

China’s Global Public Opinion War with the United States and the West

/our-media/indepth/2024/08/chinas-global-public-opinion-war

China’s global propaganda is covert and overt, digital and analog. Developing informed policy responses requires studying the totality of Beijing’s propaganda.

social media tactics. The third is an overreliance on digital tools and big data analytics to understand Beijing’s behavior. Although important, these narrowly focused — or “siloed” — examinations

Sources for Police Use of Force Data

/our-media/indepth/2022/07/sources-for-police-use-of-force-data

Daniel S. Lawrence and Hannah McLaurin provide a variety of resources to help analysts and policymakers find data on police use of force.

Sources for Police Use of Force Data Daniel S. Lawrence and Hannah McLaurin provide a variety of resources to help analysts and policymakers find data on police use of force. /images/InDepth/Cop%20in%20Mask%20resized.jpg Sources for Police Use of Force Data Daniel S. Lawrence & Hannah McLaurin Daniel Lawrence is a Research Scientist Center for CNA’s Justice Research and Innovation. Hannah McLaurin is a CNA System Engineer for CNA's Center for Data Management and Analytics . Recent social movements for police reform have highlighted the lack of data collected or publicly available

ai with ai: Slightly Unconscionable

/our-media/podcasts/ai-with-ai/season-5/5-10

Andy and Dave discuss the latest in AI news and research, including a GAO report on AI – Status of Developing and Acquiring Capabilities for Weapon Systems [1:01]. The U.S. Army has awarded a contract for the demonstration of an offensive drone swarm capability (the HIVE small Unmanned Aircraft System), seemingly similar but distinct from DARPA’s OFFSET demo [4:11]. A ‘pitch deck’ from Clearview AI reveals their intent to expand beyond law enforcement and aiming to have 100B facial photos in its database within a year [5:51]. Tortoise Media releases a global AI index that benchmarks nations based on their level of investment, innovation, and implementation of AI [7:57]. Research from UC Berkeley and the University of Lancaster shows that humans can no longer distinguish between real and fake (generated by GANs) faces [10:30]. MIT, Aberdeen, and the Centre of Governance of AI look at trends of computation in machine learning, identifying three eras and trends, including a ‘large-scale model’ trend where large corporations use massive training runs [13:37]. A tweet from the chief scientist at OpenAI, speculating on the ‘slightly conscious’ attribute of today’s large neural networks, sparks much discussion [17:23]. While a white paper in the International Journal of Astrobiology examines what intelligence might look like at the planetary level, placing Earth as an immature Technosphere [19:04]. And Kush Varchney at IBM publishes for open access a book on Trustworthy Machine Learning, examining issues of trust, safety, and much more [21:29]. Finally, CNA Russia Studies Program member Sam Bendett returns for a quick update on autonomy and AI in the Ukraine-Russia conflict [23:30].

Technical paper Compute trends across three eras of machine learning Database of milestone ML models Visualization of Parameter, Compute and Data Trends in Machine Learning ... enthusiasts sign up to repel Russian forces Analytics Insight: AI-related companies and their reactions Nando de Freitas’s Tweet on “AI community’s role” Small Drones

ai with ai: AI with AI: Montezuma’s Regulation

/our-media/podcasts/ai-with-ai/season-2/2-8

This week, Andy and Dave discuss the US Department of Commerce’s announcement to consider regulating AI as an export; counter to that idea, Amazon makes freely available 45+ hours of training materials on machine learning, with tailored learning paths; Oren Etzioni proposes ideas for broader regulation of AI research, that attempts to balance the benefits with the potential harms; DARPA tests its CODE program for autonomous drone operations in the presence of GPS and communications jamming; a Chinese researcher announces the use of CRISPR to produce the first gene-edited babies; and the 2018 ACM Gordon Bell Prize goes to Lawrence Berkeley National Lab for achieving the first exa-scale (10^18) application, running on over 27,000 NVIDIA GPUs. Uber’s OpenAI announces advances in exploration and curiosity of an algorithm that help it “win” Montezuma’s Revenge. Research from Facebook AI suggests that pre-training convolutional neural nets may provide fewer benefits over random initialization than previously thought. Google Brain examines how well ImageNet architectures transfer to other tasks. A paper from INDOPACOM describes the exploitation of big data for special operations forces. And Yuxi Li publishes a technical paper on deep reinforcement learning. And a recent paper explores self-organized criticality as a fundamental property of neural systems. Christopher Bishop’s Pattern Recognition and Machine Learning are available online, and the Architects of Intelligence provides one-on-one conversations with 23 AI researchers. Maxim Pozdorovkin releases “The Truth About Killer Robots” on HBO, and finally, a Financial Times article over-hypes (anti-hypes?) a questionable graph on Chinese AI investments.

initialization than previously thought. Google Brain examines how well ImageNet architectures transfer to other tasks. A paper from INDOPACOM describes the exploitation of big data for special operations ... babies 2018 ACM Gordon Bell Prize goes to “Exa-Scale Deep Learning for Climate Analytics" Topics Montezuma’s Revenge Solved by   Go-Explore   |   Video Rethinking ImageNet Pre-training Do Better ImageNet Models Transfer Better? Things of the Week Report of the Week   -   Exploitation of Big Data for Special Operations Forces Technical Paper of the Week -   Deep

cna talks: A New Tool to Protect First Responders

/our-media/podcasts/cna-talks/2024/01/a-new-tool-to-protect-first-responders

As cities across the country become more networked and connected with smart sensors, more data is available to first responders than ever before. But how can this data be interpreted efficiently in emergencies where every second counts? In this episode, John Crissman and Shaelynn Hales from CNA and Godfrey Nolan, founder and CEO of RIIS LLC, join the show. We discuss their award-winning First Responder Awareness Monitoring during Emergencies (FRAME) System, which takes in data from these sensors, uses machine learning to interpret the information, and aggregates that into a common data view to increase emergency situational awareness.

of CNA’s Center for Data Management Analytics. She is an expert in systems engineering, data management, data analytics, and integrated program management support. John Crissman   is a Research Analyst in CNA’s Center for Data Management Analytics. He is an expert in artificial intelligence (AI), machine learning (ML), and natural language processing. Godfrey Nolan is the Founder and President ... A New Tool to Protect First Responders As cities across the country become more networked and connected with smart sensors, more data is available to first responders than ever before. But how can

cna talks: Moving at the Speed of Innovation — Regulating Package Delivery Drones

/our-media/podcasts/cna-talks/2023/08/moving-at-the-speed-of-innovation---regulating-package-delivery-drones

Companies, including Amazon, UPS, and Domino's are all investing in package delivery drones. These systems represent a significant paradigm shift from the current air traffic control model. With the private sector moving at the speed of innovation, the government will need new tools to regulate this new airspace. In this episode, we discuss CNA’s new agent-based model, UAS Cooperative Airspace Traffic Simulation (UCATS™), and how it can help the FAA and local stakeholders fairly regulate package delivery drone operations.

operations. Moving at the Speed of Innovation — Regulating Package Delivery Drones Guest Biographies  Rebekah Yang   is Systems Engineer with CNA’s Center for Data Management Analytics and the lead engineer on this model. She is an artificial intelligence and machine learning expert for the Federal Aviation Administration's Office of NextGen and a data visualization and modeling specialist