By John P. Desmond, AI Trends Editor
As wildfires rage in the west and the density of smoke is blocking out the sun in many areas, attention is turning to the fight against climate change and whether AI can make a difference.
Climate Change AI is among the initiatives working on it. The group of AI researchers is exploring solutions to climate change and related issues such as food insecurity and human displacement. The group in the past month has discussed what type of startups can combat climate change; they are assembling a dataset wish list from researchers to inform the data used to train models, according to an account in VentureBeat.
One effort is from WattTime, a nonprofit organization that aims to reduce the carbon footprint of a household by automating when electric vehicles, thermostats and appliances are active based on when renewable energy is available. Algorithms to determine those times are trained using data from the continuous pollution monitoring system of the EPA. The technology is available in California, which produces one-third of its power from renewable energy.
“Nobody knows about the U.S. continuous emissions monitoring system, but it’s been live since the ’70s, and it’s why organizations like mine can write increasingly sophisticated AI algorithms to integrate more renewable energy and do what we do,” stated WattTime Cofounder and Executive Director Gavin McCormick. WattTime received a grant last year from Google.org’s AI Impact Challenge, to see whether computer vision can be used to track power plant emissions outside the US from satellite images.
Moreover, McCormick worked with former US Vice President Al Gore on the July announcement of Climate Trace, a coalition attempting to build a tool to track human-cause greenhouse gas emissions from all over the planet.
The Intergovernmental Panel on Climate Change (IPCC), said to be the world’s leading scientific body on the climate crisis, has advised that emissions of accumulated greenhouse gases (GHGs) need to be cut in half by 2030 and reach net-zero emissions by 2050, to avoid the worst effects of global warming.
“We are honored to announce that a powerful new tool will soon be joining the climate fight,” Gore wrote in a recent account in Medium. “Climate TRACE is a coalition creating a high-tech solution to independently detect emissions and where they’re coming from, everywhere in the world, in real time. It’s a feat that’s never before been possible — until now.”
In addition to WattTime, founding members include Blue Sky Analytics, CarbonPlan, Carbon Tracker, Earthrise Alliance, Hudson Carbon, Hypervine, OceanMind, and Rocky Mountain Institute.
The coalition plans to leverage advanced AI, satellite image processing, machine learning, and land- and sea-based sensors to monitor GHG emissions from every sector and in every part of the world. The intent is to monitor human-caused GHG emissions worldwide with a granular focus down to specific targets including power plants, ships and factories.
The group hopes to present its emissions data in Glasgow, Scotland, next year when countries are scheduled to gather to renew their commitments to the Paris Agreement, signed in 2016 to address greenhouse gas emissions mitigation. Under US President Donald Trump, the US announced in June 2017 it would be withdrawing from the agreement.
Current Emission Reporting System an Unreliable Patchwork
The current system of tracking greenhouse gas emissions is a patchwork of infrequent self-reporting by companies and countries, without reliable third-party verification, and long lags in reporting. “We can only manage what we can measure,” Gore wrote. “Countries, companies, and leaders worldwide want to solve the climate crisis, but lack the tools to do so quickly and effectively.”
The global sensor network to include satellites and ground- and sea-based instruments, all connected to an AI engine built for the purpose, “Emissions have nowhere to hide,” Gore stated. Scientists, regulators, the news media, citizen activities, investors and business leaders will see where the GHG emissions are coming from, and whether it’s increasing or decreasing.
Recent technology advances have made this solution possible. The group built a smaller version of the project to measure power plant emissions; the experience shows the range of components. The effort combined imagery from: multiple satellite constellations (like the European Space Agency’s Sentinel 2 mission), AI algorithms from experts in computer vision (such as Pixel Scientia Labs), data pipeline engineering (Google.org), power plant databases (World Resources Institute), remote sensing (Valence Strategic), power systems modeling (WattTime), weather adjustments and power plant cooling systems (Carbon Tracker), and more.
“We envision a future in which low- and zero-carbon energy is the norm. We believe Climate TRACE will be an integral part of making that future become reality, and we’re getting right to work,” Gore wrote, then issuing a challenge to the industry: “Today, we issue a call to action: If you’re working in a field that touches on emissions monitoring — whether you have AI expertise, satellite sensor networks, or other global sensor or emissions data networks — we want to hear from you.”
So you have been called. Visit Climate Trace.
Efforts to Combat Climate Change to Recognize
Efforts to combat climate change have been taking place and deserve recognition.
Google is using machine learning to lower the energy use of its data centers. The London-based AI unit DeepMind is using information collected by sensors to reduce energy use for cooling for up to 40%, according to a recent account in Thrive. Plans are to apply the system to clean energy output so Google can better manage its conventional energy needs.
The company Hypergiant of Austin, Texas, is growing algae so it can absorb carbon dioxide and give off oxygen. Naturally-growing algae grows out of control. The company’s scientists have developed an AI unit called the Eos Bioreactor that can regulate the growth of the algae and optimize its carbon-absorbing properties. The size of a refrigerator, the unit is said to be 400 times more effective at capturing carbon than trees in the same area.
Green Horizons, an IBM research initiative, is using cognitive computing and the internet of things (IoT) to analyze climate change data. Cognitive computing is being paired with IoT to predict pollution rates in Beijing. The system uses machine learning to ingest data from sources such as meteorological satellites and traffic cameras to constantly learn and adjust the predictive models. It is able to forecast pollution 72 hours in advance, with an accuracy down to the nearest kilometer on where the pollution is coming from and where it will likely go.
Beijing is using this methodology with the goal of reducing pollution levels ahead of the 2022 Winter Olympics. It can use the predictions to implement policies such as temporarily restricting industrial activity or limiting traffic and construction. It is modeling hypothetical scenarios to test the effectiveness of the interventions.
How 5G Will Impact Customer Experience?
5G is the breakthrough technology promised to bring new innovations, change the way people are traversing through the Internet with its faster connection speeds, lower latency, high bandwidth, and ability to connect one million devices per square kilometre. Telcos are deploying 5G to enhance our day-to-day lives.
“When clubbed with other technologies like Artificial Intelligence, Internet of Things (IoT), it could mean a lot to a proliferation of other technologies like AR/VR, data analytics.”
5G can be a boon for businesses with the delivery of increased reliability, efficiency and performance if it can be used to drive more value to the customers as well as the business stakeholders and meet their expectations with the help of digital technologies as mentioned below:
Consumer Expectations are on the Rise
In modern days, customer service teams provide and manage customer support via call centres and digital platforms. The rollout of 5G is expected to unleash more benefits with a positive impact on customer service as they improve their present personalized service offerings to customers and allow it to further create new solutions that could develop their customer engagement to win great deals.
For instance, salespeople in a retail store are being imbibed with layers of information about customers’ behaviour and choices that will help them build a rich and tailored experience for the customers walking down the store.
Video Conferencing/streaming is Just a Few Clicks Away
Video support is considered to be a critical part of Consumer Experience (CX) and will open new avenues for consumer-led enterprises.
“As per a survey conducted by Oracle with 5k people, 75% of people understand the efficiency and value of video chat and voice calls.”
CX representatives used the video support feature to troubleshoot highly technical situations through video chat and screen sharing options with few clicks, potentially reducing the number of in-house technician visits during critical situations like coronavirus pandemic.
Also, nowadays video conferencing is facilitated with an option to record a quick instant video describing the process/solution and discarding the long process of sending step-by-step emails. Enterprises can develop advanced user guide for troubleshooting issues featuring video teasers for resolving common problems.
However, high-definition video quality is preferable for video conferencing, chat and demands for an uninterrupted network with smooth video streaming. This means operators need to carry out network maintenance activities on regular intervals to check whether there is any kind of 5G PIM formation on these network cell towers that could reduce receive sensitivity and performance, thereby deteriorating network speed, video resolution etc.
Thus, PIM testing becomes critical for delivering enhanced network services without interference, necessary for high-resolution online video conferencing, chats, and many more.
Increased Smart Devices and the Ability to Troubleshoot via Self-Service
The inception of 5G will give a boost to the IoT and smart device market which is already growing.
These smart devices IoT connections are expected to become twice in number between 2019 and 2025 i.e. more than 25Bn as per the GSM association which is an industry organization representing telecom operators across the globe.
With lower latency and improvisation in reliability, 5G has a lot more to offer as it connects a large number of devices. This will ultimately curb the manpower needed for customer support thereby reducing labour costs for the enterprise. Moreover, these IoT connected devices and high-speed network of 5G permit consumers to self-troubleshoot these devices at their own homes.
In order to facilitate these high-resolution networks, telecom operators need to perform 5G network testing and identify issues, take corrective actions that could improve their network and integrate with advanced capabilities, making it more efficient than previous connections with the wider network coverage.
Enhanced Augmented Reality (AR) / Virtual Reality (VR) Capabilities
As these tools are being widely used, customers are provided with virtual stores or immersive experiences using AR to view a sneak peek of the products in their house in real-time.
“‘Augmented Retail: The New Consumer Reality’ study by Nielsen in 2019 suggested that AR/VR has created a lot of interest in people and they are willing to use these technologies to check out products.”
Analysis of Bulk Data With Big Data Analytics
Enterprises have to deal with a huge volume of data daily. 5G has the ability to collect these data and with its advanced network connectivity across a large number of devices, it delivers faster data analytics too.
Companies will be able to process this vast amount of unstructured data sets combined with Artificial Intelligence (AI) to extract meaningful insights and use them for drafting business strategies like using customer behaviour data sets to study their buying behaviour and targeting such segment with customized service offerings as per their requirement.
As per Ericsson’s AI in networks report, 68% of Communications Service Providers (CSPs) believe improving CX is a business objective while more than half of them already believe AI will be a key technology that will assist in improving the overall CX. Thus, big data analytics will be crucial for harnessing all new data and enhance the customer experience.
Looking from a CX point of view, 5G benefits will far extend beyond the experience of a citizen. Real-time decisions will accelerate with the prevalence of 5G and application of other new-age technologies like AI, ML, IoT, etc. As 5G deployment will continue to grow, so is the transition of each trending processes mentioned above that will ultimately improve your business in terms of productivity, gain a large customer base and bring more revenues.
Resiliency And Security: Future-Proofing Our AI Future
By Allison Proffitt, AI Trends
On the first day of the Second Annual AI World Government conference and expo held virtually October 28-30, a panel moderated by Robert Gourley, cofounder & CTO of OODA, raised the issue of AI resiliency. Future-proofing AI solutions requires keeping your eyes open to upcoming likely legal and regulatory roadblocks, said Antigone Peyton, General Counsel & Innovation Strategist at Cloudigy Law. She takes a “use as little as possible” approach to data, raising questions such as: How long do you really need to keep training data? Can you abstract training data to the population level, removing some risk while still keeping enough data to find dangerous biases?
Stephen Dennis, Director of Advanced Computing Technology Centers at the U.S. Department of Homeland Security, also recommended a forward-looking posture, but in terms of the AI workforce. In particular, Dennis challenged the audience to consider the maturity level of the users of new AI technology. Full automation is not likely a first AI step, he said. Instead, he recommends automating slowly, bringing the team along. Take them a technology that works in the context they are used to, he said. They shouldn’t need a lot of training. Mature your team with the technology. Remove the human from the loop slowly.
Of course, some things will never be fully automated. Brian Drake, U.S. Department of Defense, pointed out that some tasks are inherently human-to-human interactions—such as gathering human intelligence. But AI can help humans do even those tasks better, he said.
He also cautioned enterprises to consider their contingency plan as they automate certain tasks. For example, we rarely remember phone numbers anymore. We’ve outsourced that data to our phones while accepting a certain level of risk. If you deploy a tool that replaces a human analytic activity, that’s fine, Drake said. But be prepared with a contingency plan, a solution for failure.
Organizing for Resiliency
All of these changes will certainly require some organizational rethinking, the panel agreed. While government is organized in a top down fashion, Dennis said, the most AI-forward companies—Uber, Netflix—organize around the data. That makes more sense, he proposed, if we are carefully using the data.
Data models—like the new car trope—begin degrading the first day they are used. Perhaps the source data becomes outdated. Maybe an edge use case was not fully considered. The deployment of the model itself may prompt a completely unanticipated behavior. We must capture and institutionalize those assessments, Dennis said. He proposed an AI quality control team—different from the team building and deploying algorithms—to understand degradation and evaluate the health of models in an ongoing way. His group is working on this with sister organizations in cyber security, and he hopes the best practices they develop can be shared to the rest of the department and across the government.
Peyton called for education—and reeducation—across organizations. She called the AI systems we use today a “living and breathing animal”. This is not, she emphasized, an enterprise-level system that you buy once and drop into the organization. AI systems require maintenance, and someone must be assigned to that caretaking.
But at least at the Department of Defense, Drake pointed out, all employees are not expected to become data scientists. We’re a knowledge organization, he said, but even if reskilling and retraining are offered, a federal workforce does not have to universally accept those opportunities. However, surveys across DoD have revealed an “appetite to learn and change”, Drake said. The Department is hoping to feed that curiosity with a three-tiered training program offering executive-level overviews, practitioner-level training on the tools currently in place, and formal data science training. He encouraged a similar structure to AI and data science training across other organizations.
Bad AI Actors
Gourley turned the conversation to bad actors. The very first telegraph message between Washington DC and Baltimore in 1844 was an historic achievement. The second and third messages—Gourley said—were spam and fraud. Cybercrime is not new and it is absolutely guaranteed in AI. What is the way forward, Gourley asked the panel.
“Our adversaries have been quite clear about their ambitions in this space,” Drake said. “The Chinese have published a national artificial intelligence strategy; the Russians have done the same thing. They are resourcing those plans and executing them.”
In response, Drake argued for the vital importance of ethics frameworks and for the United States to embrace and use these technologies in an “ethically up front and moral way.” He predicted a formal codification around AI ethics standards in the next couple of years similar to international nuclear weapons agreements now.
AI Projects Progressing Across Federal Government Agencies
By AI Trends Staff
Government agencies are gaining experience with AI on projects, with practitioners focusing on defining the project benefit and the data quality is good enough to ensure success. That was a takeaway from talks on the opening day of the Second Annual AI World Government conference and expo held virtually on October 28.
Wendy Martinez, PhD, director of the Mathematical Statistics Research Center, with the Office of Survey Methods Research in the US Bureau of Labor Statistics, described a project to use natural language understanding AI to parse text fields of databases, and automatically correlate them to job occupations in the federal system. One lesson learned was despite interest in sharing experience with other agencies, “You can’t build a model based on a certain dataset and use the model somewhere else,” she stated. Instead, each project needs its own source of data and model tuned to it.
Renata Miskell, Chief Data Officer in the Office of the Inspector General for the US Department of Health and Human Services, fights fraud and abuse for an agency that oversees over $1 trillion in annual spending, including on Medicare and Medicaid. She emphasized the importance of ensuring that data is not biased and that models generate ethical recommendations. For example, to track fraud in its grant programs awarding over $700 billion annually, “It’s important to understand the data source and context,” she stated. The unit studied five years of data from “single audits” of individual grant recipients, which included a lot of unstructured text data. The goal was to pass relevant info to the audit team. “It took a lot of training, she stated. “Initially we had many false positives.” The team tuned for data quality and ethical use, steering away from blind assumptions. “If we took for granted that the grant recipients were high risk, we would be unfairly targeting certain populations,” Miskell stated.
In the big picture, many government agencies are engaged in AI projects and a lot of collaboration is going on. Dave Cook is senior director of AI/ML Engineering Services for Figure Eight Federal, which works on AI projects for federal clients. He has years of experience working in private industry and government agencies, mostly now the Department of Defense and intelligence agencies. “In AI in the government right now, groups are talking to one another and trying to identify best practices around whether to pilot, prototype, or scale up,” he said. “The government has made some leaps over the past few years, and a lot of sorting out is still going on.”
Ritu Jyoti, Program VP, AI Research and Global AI Research lead for IDC consultants, program contributor to the event, has over 20 years of experience working with companies including EMC, IBM Global Services, and PwC Consulting. “AI has progressed rapidly,” she said. From a global survey IDC conducted in March, business drivers for AI adoption were found to be better customer experience, improved employee productivity, accelerated innovation and improved risk management. A fair number of AI projects failed. The main reasons were unrealistic expectations, the AI did not perform as expected, the project did not have access to the needed data, and the team lacked the necessary skills. “The results indicate a lack of strategy,” Joti stated.
David Bray, PhD, Inaugural Director of the nonprofit Atlantic Council GeoTech Center, and a contributor to the event program, posted questions on how data governance challenges the future of AI. He asked what questions practitioners and policymakers around AI should be asking, and how the public can participate more in deciding what can be done with data. “You choose not to be a data nerd at your own peril,” he said.
Anthony Scriffignano, PhD, senior VP & Chief Data Scientist with Dun & Bradstreet, said in the pandemic era with many segments of the economy shut down, companies are thinking through and practicing different ways of doing things. “We sit at the point of inflection. We have enough data and computer power to use the AI techniques invented generations ago in some cases,” he said. This opportunity poses challenges related to what to try and what not to try, and “sometimes our actions in one area cause a disruption in another area.”
AI World Government continues tomorrow and Friday.
(Ed. Note: Dr. Eric Schmidt, former CEO of Google is now chair of the National Security Commission on AI, today was involved in a discussion, Transatlantic Cooperation Around the Future of AI, with Ambassador Mircea Geoana, Deputy Secretary General, North Atlantic Treaty Organization, and Secretary Robert O. Work, vice chair of the National Security Commission. Convened by the Atlantic Council, the event can be viewed here.)
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