PEARC21 Plenary Session: AI for Innovative Social Work

By Ken Chiacchia, Pittsburgh Supercomputing Center/XSEDE

July 21, 2021

AI analysis of social media poses a double-edged sword for social work and addressing the needs of at-risk youths, said Desmond Upton Patton, senior associate dean, Innovation and Academic Affairs, Columbia University. Speaking in the opening plenary session of the PEARC21 conference, Patton noted that on the one hand, it offers a powerful potential tool for understanding and preventing violence. On the other hand, when applied thoughtlessly or without social context, it runs a high risk of false inference, over-surveillance and further victimizing the communities it intends to help.

The PEARC conference series provides a forum for discussing challenges, opportunities and solutions among the broad range of participants in the research computing community. This community-driven effort builds on successes of the past, and aims to grow and be more inclusive by involving additional local, regional, national and international cyberinfrastructure and research computing partners spanning academia, government and industry. PEARC21, Evolution Across All Dimensions, was offered this year as a virtual event (July 19-22).

Selective Reporting, Building Mythology

“I’m a social worker at heart; I have gone on an eight-year journey to understand social media in an environmental context,” Patton said. His work has focused on Gakirah Barnes, a Chicago teen who had been largely demonized and mythologized in the press as the archetypal “gang banger.”

Certainly, like teens everywhere today, youths in the heavily Black and Latinx neighborhoods of the South and West sides of Chicago live a large portion of their lives on social media. Gang members of rival crews act out their grievances online, and sometimes those arguments translate into real-world violence. But selective reporting on seemingly aggressive tweets often misses the neighborhood culture and personal history needed to make sense of those tweets. Another challenge is determining which aggressive tweets defuse emotions and which build on them; Some teens who brag about gang membership and violence online are mostly following Disney princesses.

“Even if you’re from the same neighborhood, you might not have the same interpretation of what’s happening online,” Patton said. In particular, selective reporting of angry grief can seem like imminent violence when stripped of the context of intervening tweets, let alone personal history.

Barnes was notorious, at least in the Chicago press. The facts are difficult to glean. She was credited with killing or shooting 20 people, but had never been arrested. She was murdered in 2014 near her home. And she was a prolific Twitter user, among the 98th percentile in terms of tweets.

“I’ve studied her tweets online and I’m still struggling as a researcher to demarcate what I read about her and what I think about her,” Patton said. Analysis of online behavior “is not easy and should not be done lightly … I made lots of mistakes in my interpretation of Gakirah that could have been really misused.”

CASM: Applying Social Context to NLP

As do many natural language processing projects, Patton’s group’s CASM method—Contextual Analysis of Social Media—started with expert annotation of the content of tweets. He turned to young people living in the affected communities and to students. Even so, baseline impressions, without context, often missed important details. Adding contextual information such as the original post being reacted to, facts about the author and their peer network, offline events, virality and engagement were needed to provide accurate annotation.

Working with Kathleen McKeown of Columbia’s Natural Language Processing Group and Shih-Fu Chang of its Digital Video Multimedia Laboratory, Patton started with an initial labeling of social media entries as “loss,” “aggression” or “other,” the latter including a number of concepts from mood to neighborhood to health to substance abuse. In a series of reports, the team began with a training dataset of 616 tweets, a development dataset of 102 tweets, and a test of 102 tweets. Eventually the work expanded to utilize 4,936 labeled tweets by Barnes and her top communicators to analyze about a million unlabeled related tweets from 279 Twitter users.

“In the initial run, none of the gold-standard tools could work because they could not understand the context or language,” Patton said. Many posts the experts scored as loss were instead labeled as aggressive or threatening. “It was scary having a tool that was misfiring in this way.”

The initial algorithm, when optimized using speech tags developed from qualitative analysis, performed at an F-measure (a statistical measure of accuracy that takes into account both the ratio of true positives to true positives plus false negatives and the ratio of true positives to true plus false positives) of 62 percent. Expanding the dataset improved this, but only to an F-measure of 70 percent.

“Again, what does it mean to have an accurate tool in this particular context, and should we even use this tool at all” given the modest accuracy, he asked. Any such tool could easily be misused, particularly given the uneven way in which online surveillance has been applied to Black versus White youths. Still, he added, parents in communities affected by gang violence “usually do not care how you do it” if you keep their kids safe. “You rarely find an ethical framework that toggles between these issues.”

Patton and his collaborators are continuing the work, trying to find ways of bringing the accuracy of their ML algorithms up to an acceptable level—as well as defining what is acceptable, and what uses are ethical. They will share code—though not social media data, to protect study subjects’ identities—with researchers interested in the problem.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Rockport Networks Launches 300 Gbps Switchless Fabric, Reveals 396-Node Deployment at TACC

October 27, 2021

Rockport Networks emerged from stealth this week with the launch of its 300 Gbps switchless networking architecture focused on the needs of the high-performance computing and the advanced-scale AI market. Early customers Read more…

AWS Adds Gaudi-Powered, ML-Optimized EC2 DL1 Instances, Now in GA

October 27, 2021

As machine learning becomes a dominating use case for local and cloud computing, companies are racing to provide solutions specifically optimized and accelerated for AI applications. Now, Amazon Web Services (AWS) is int Read more…

Fireside Chat with LBNL’s Advanced Quantum Testbed Director

October 26, 2021

Last week, Irfan Siddiqi led a “fireside chat” with a few media and analysts to introduce the Department of Energy’s relatively new Advanced Quantum Testbed (AQT), which is based at Lawrence Berkeley National Labor Read more…

Graphcore Introduces Larger-Than-Ever IPU-Based Pods

October 22, 2021

After launching its second-generation intelligence processing units (IPUs) in 2020, four years after emerging from stealth, Graphcore is now boosting its product line with its largest commercially-available IPU-based sys Read more…

Quantum Chemistry Project to Be Among the First on EuroHPC’s LUMI System

October 22, 2021

Finland’s CSC has just installed the first module of LUMI, a 550-peak petaflops system supported by the European Union’s EuroHPC Joint Undertaking. While LUMI -- pictured in the header -- isn’t slated to complete i Read more…

AWS Solution Channel

Royalty-free stock illustration ID: 577238446

Putting bitrates into perspective

Recently, we talked about the advances NICE DCV has made to push pixels from cloud-hosted desktops or applications over the internet even more efficiently than before. Read more…

Killer Instinct: AMD’s Multi-Chip MI200 GPU Readies for a Major Global Debut

October 21, 2021

AMD’s next-generation supercomputer GPU is on its way – and by all appearances, it’s about to make a name for itself. The AMD Radeon Instinct MI200 GPU (a successor to the MI100) will, over the next year, begin to power three massive systems on three continents: the United States’ exascale Frontier system; the European Union’s pre-exascale LUMI system; and Australia’s petascale Setonix system. Read more…

Rockport Networks Launches 300 Gbps Switchless Fabric, Reveals 396-Node Deployment at TACC

October 27, 2021

Rockport Networks emerged from stealth this week with the launch of its 300 Gbps switchless networking architecture focused on the needs of the high-performance Read more…

AWS Adds Gaudi-Powered, ML-Optimized EC2 DL1 Instances, Now in GA

October 27, 2021

As machine learning becomes a dominating use case for local and cloud computing, companies are racing to provide solutions specifically optimized and accelerate Read more…

Fireside Chat with LBNL’s Advanced Quantum Testbed Director

October 26, 2021

Last week, Irfan Siddiqi led a “fireside chat” with a few media and analysts to introduce the Department of Energy’s relatively new Advanced Quantum Testb Read more…

Killer Instinct: AMD’s Multi-Chip MI200 GPU Readies for a Major Global Debut

October 21, 2021

AMD’s next-generation supercomputer GPU is on its way – and by all appearances, it’s about to make a name for itself. The AMD Radeon Instinct MI200 GPU (a successor to the MI100) will, over the next year, begin to power three massive systems on three continents: the United States’ exascale Frontier system; the European Union’s pre-exascale LUMI system; and Australia’s petascale Setonix system. Read more…

D-Wave Embraces Gate-Based Quantum Computing; Charts Path Forward

October 21, 2021

Earlier this month D-Wave Systems, the quantum computing pioneer that has long championed quantum annealing-based quantum computing (and sometimes taken heat fo Read more…

LLNL Prepares the Water and Power Infrastructure for El Capitan

October 21, 2021

When it’s (ostensibly) ready in early 2023, El Capitan is expected to deliver in excess of two exaflops of peak computing power – around four times the powe Read more…

Intel Reorgs HPC Group, Creates Two ‘Super Compute’ Groups

October 15, 2021

Following on changes made in June that moved Intel’s HPC unit out of the Data Platform Group and into the newly created Accelerated Computing Systems and Graphics (AXG) business unit, led by Raja Koduri, Intel is making further updates to the HPC group and announcing... Read more…

Quantum Workforce – NSTC Report Highlights Need for International Talent

October 13, 2021

Attracting and training the needed quantum workforce to fuel the ongoing quantum information sciences (QIS) revolution is a hot topic these days. Last week, the U.S. National Science and Technology Council issued a report – The Role of International Talent in Quantum Information Science... Read more…

Enter Dojo: Tesla Reveals Design for Modular Supercomputer & D1 Chip

August 20, 2021

Two months ago, Tesla revealed a massive GPU cluster that it said was “roughly the number five supercomputer in the world,” and which was just a precursor to Tesla’s real supercomputing moonshot: the long-rumored, little-detailed Dojo system. Read more…

Esperanto, Silicon in Hand, Champions the Efficiency of Its 1,092-Core RISC-V Chip

August 27, 2021

Esperanto Technologies made waves last December when it announced ET-SoC-1, a new RISC-V-based chip aimed at machine learning that packed nearly 1,100 cores onto a package small enough to fit six times over on a single PCIe card. Now, Esperanto is back, silicon in-hand and taking aim... Read more…

US Closes in on Exascale: Frontier Installation Is Underway

September 29, 2021

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, held by Zoom this week (Sept. 29-30), it was revealed that the Frontier supercomputer is currently being installed at Oak Ridge National Laboratory in Oak Ridge, Tenn. The staff at the Oak Ridge Leadership... Read more…

Intel Reorgs HPC Group, Creates Two ‘Super Compute’ Groups

October 15, 2021

Following on changes made in June that moved Intel’s HPC unit out of the Data Platform Group and into the newly created Accelerated Computing Systems and Graphics (AXG) business unit, led by Raja Koduri, Intel is making further updates to the HPC group and announcing... Read more…

Ahead of ‘Dojo,’ Tesla Reveals Its Massive Precursor Supercomputer

June 22, 2021

In spring 2019, Tesla made cryptic reference to a project called Dojo, a “super-powerful training computer” for video data processing. Then, in summer 2020, Tesla CEO Elon Musk tweeted: “Tesla is developing a [neural network] training computer... Read more…

Intel Completes LLVM Adoption; Will End Updates to Classic C/C++ Compilers in Future

August 10, 2021

Intel reported in a blog this week that its adoption of the open source LLVM architecture for Intel’s C/C++ compiler is complete. The transition is part of In Read more…

Hot Chips: Here Come the DPUs and IPUs from Arm, Nvidia and Intel

August 25, 2021

The emergence of data processing units (DPU) and infrastructure processing units (IPU) as potentially important pieces in cloud and datacenter architectures was Read more…

AMD-Xilinx Deal Gains UK, EU Approvals — China’s Decision Still Pending

July 1, 2021

AMD’s planned acquisition of FPGA maker Xilinx is now in the hands of Chinese regulators after needed antitrust approvals for the $35 billion deal were receiv Read more…

Leading Solution Providers

Contributors

HPE Wins $2B GreenLake HPC-as-a-Service Deal with NSA

September 1, 2021

In the heated, oft-contentious, government IT space, HPE has won a massive $2 billion contract to provide HPC and AI services to the United States’ National Security Agency (NSA). Following on the heels of the now-canceled $10 billion JEDI contract (reissued as JWCC) and a $10 billion... Read more…

Intel Unveils New Node Names; Sapphire Rapids Is Now an ‘Intel 7’ CPU

July 27, 2021

What's a preeminent chip company to do when its process node technology lags the competition by (roughly) one generation, but outmoded naming conventions make i Read more…

Quantum Roundup: IBM, Rigetti, Phasecraft, Oxford QC, China, and More

July 13, 2021

IBM yesterday announced a proof for a quantum ML algorithm. A week ago, it unveiled a new topology for its quantum processors. Last Friday, the Technical Univer Read more…

The Latest MLPerf Inference Results: Nvidia GPUs Hold Sway but Here Come CPUs and Intel

September 22, 2021

The latest round of MLPerf inference benchmark (v 1.1) results was released today and Nvidia again dominated, sweeping the top spots in the closed (apples-to-ap Read more…

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

Frontier to Meet 20MW Exascale Power Target Set by DARPA in 2008

July 14, 2021

After more than a decade of planning, the United States’ first exascale computer, Frontier, is set to arrive at Oak Ridge National Laboratory (ORNL) later this year. Crossing this “1,000x” horizon required overcoming four major challenges: power demand, reliability, extreme parallelism and data movement. Read more…

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

D-Wave Embraces Gate-Based Quantum Computing; Charts Path Forward

October 21, 2021

Earlier this month D-Wave Systems, the quantum computing pioneer that has long championed quantum annealing-based quantum computing (and sometimes taken heat fo Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire