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Artificial intelligence has been hogging headlines around the world in recent months. In late March 2023, an unprecedented coalition of tech CEOs signed an open letter calling for a moratorium on AI training. The race to empower powerful artificial minds should be paused, argued signatories (including Elon Musk) to give humanity time to review and reassess the potential risks of developing “human-competitive intelligence”–intelligence that “no one–not even their creators–can understand, predict, or reliably control.” Concerns about the unchecked rise of AI are not new, and global media is increasingly sounding the alarm, citing concerns that range from invasion of privacy to an existential threat to human existence. Weighing in on this with compelling new evidence around the “unintended consequences” of AI is research by Goizueta’s Ramnath Chellappa and Information Systems PhD candidate, Jonathan Gomez Martinez. Uncovering the Threat Their paper, Content Moderation and AI: Impact on Minority Communities, takes a hard look at how the use of AI in social media could disadvantage LGBTQ+ users. And what they find is worrying. Chellappa, who is Goizueta Foundation Term Professor of Information Systems & Operations Management, explains that he and Gomez Martinez homed in on Twitter to explore how unchecked artificial language moderation might (mistakenly) censor the use of “otherwise toxic” language by failing to understand the context or nuanced use of the LGBTQ+ lexicon. Examples of this include “reclaimed language”—verbiage that would be a slur in other contexts—but is reclaimed and prosocial if used by the originally targeted community. Their paper, Content Moderation and AI: Impact on Minority Communities, takes a hard look at how the use of AI in social media could disadvantage LGBTQ+ users. And what they find is worrying. Chellappa, who is Goizueta Foundation Term Professor of Information Systems & Operations Management, explains that he and Gomez Martinez homed in on Twitter to explore how unchecked artificial language moderation might (mistakenly) censor the use of “otherwise toxic” language by failing to understand the context or nuanced use of the LGBTQ+ lexicon. Examples of this include “reclaimed language”—verbiage that would be a slur in other contexts—but is reclaimed and prosocial if used by the originally targeted community. “This is a community that has ‘reclaimed’ certain words and expressions that might be considered offensive in other contexts. Terms like ‘queer’ are used within the community both in jest and as a marker of identity and belonging. But if used by those outside the community, this kind of language could be deemed inflammatory or offensive.” Gomez Martinez adds: “We wanted to measure the extent to which AI’s lack of a nuanced understanding of what is ‘acceptable’ affects minority users’ online interactions. As humans, we understand that marginalized communities have long used ‘reclaimed words’ both in jest and as a kind of rallying cry. Our intuition was that the machine simply wouldn’t understand this without context—context that is more immediately apparent to people.” Determining the Impact of AI-Based Moderation To test this, he and Chellappa looked at data from social media behemoth, Twitter. During the pandemic in 2020, the platform made a significant shift to AI-based content moderation to accommodate stay-at-home measures. Data from Twitter’s proprietary Academic Research API afforded Gomez Martinez and Chellappa access to a complete listing of historical tweets and replies before, during and after this period. Together they analyzed a total of 3.8 million interactions (1.8 million tweets and 2.0 million replies) from a panel of 2,751 users, of which 1,224 self-identified as LGBTQ+ in their Twitter bios. Their study ran over four months, from January to May 2020, before, during and after the switch to machine-based moderation. Using the same tools that Twitter moderators deploy to moderate interactions, Gomez Martinez and Chellappa were able to measure any increase or decrease in pro-social, in-group teasing and toxic language among LGBTQ+ users: terms such as “bitch” or “queer,” which research shows to be a form of ritualized insults—dubbed “reading” by the community—which can appear inappropriate or incoherent to outsiders, says Chellappa. “Analyzing the language, we find a notable reduction in the use of terms that could be considered toxic. When the AI moderation is in effect, you see these users’ language become more vanilla,” he adds. Quantifiably so, in fact. Chellappa and Martinez find a 27 percent reduction in the use of reclaimed language among LGBTQ+ users. And while that doesn’t sound like much, it’s significant for the community, says Gomez Martinez. Using in-language and reading each other is one way for this marginalized group to create a sense of community and social status. Not just that, we know from research that LGBTQ+ people use slurs and insults as a way of preparing themselves emotionally and psychologically for hostile interaction with heterosexual individuals. This kind of teasing and playing helps build resilience, so any reduction in it is significant.” Jonathan Gomez Martinez Good Intentions May Breed Unexpected Consequences So what does this mean for social media, for the LGBTQ+ community or any marginalized group for that matter, that might be prone to automated censorship? And how does any of this play out in the context of broader concerns around AI? For Chellappa and Gomez Martinez, there is a major hazard in granting technology any degree of control over how human beings interact. And it’s rooted in the mismatch between good intentions and unexpected consequences. Their paper, one of the first to dig into the impact of AI on actual business and society, lays bare some of the real-world impact AI has already had on marginalized people. While this study looks at the LGBTQ+ community, it could equally apply to any group that is prone to bias or exclusion—racial minorities or any other underrepresented demographic. “Wherever you have user-generated content, you are likely to find communities with their own, unique way of interacting. We looked at LGBTQ+ Twitter users, but you could also look at the African American community, for instance.” Ramnath K. Chellapa At a time when social media platforms have become almost newslike in their influence, this is a concern. On the one hand, censoring certain demographics might earn Twitter et al an unwanted reputation for being anti-LGBTQ+ or racist, he adds. But there are even bigger stakes here than bad publicity. “Twitter has long aspired to be a kind of global town square,” says Gomez Martinez. “But you end up pretty far from that scenario if only some voices are truly heard, or if you start reinforcing biases because you are using a time-saving technology that is not equipped yet to understand the complexity and nuance of human interaction.” AI isn’t there yet, say Chellappa and Gomez Martinez. And they caution against using AI indiscriminately to expedite or streamline processes that impact human communication and interchange. If we don’t keep track of it, their research shows that AI has the potential to start dictating and moving people into normative behavior—effectively homogenizing us. And that’s a problem. Looking to know more? Ramnath Chellappa is available to speak with media. Simply click on his icon now to arrange an interview today.
Expert Insight: The Voice of Alexa: How Speech Characteristics Impact Consumer Decisions
In the 2020 film “Superintelligence,” an all-powerful artificial intelligence attempts to take over the world, and it studies an average person, played by Melissa McCarthy, to decide if humanity is worth saving. The AI is voiced by James Corden—a voice it chooses because it knows it’s one McCarthy’s character will engage with. Rajiv Garg, associate professor of Information Systems & Operations Management at Emory’s Goizueta Business School, shows the “Superintelligence” trailer before his research presentations to set the tone. Garg conducts research that explores the impact of artificial intelligence voices on consumer behavior and purchase intent, along with Haris Krijestorac, a professor at HEC Paris, and Vijay Mahajan, a professor from The University of Texas at Austin. Garg’s research began when Amazon launched celebrity voices for its Alexa device in 2019. From Samuel L. Jackson to Shaquille O’Neal, users can now get their news and entertainment, while interacting with their favorite superstars. “I questioned if certain voices could get more engagement or more purchases from consumers,” Garg says. If Alexa starts talking to you in Samuel L. Jackson’s voice, will you continue the conversation? What could Samuel L. Jackson’s voice sell you that you would buy? Garg and his team began their research by collecting more than 300 celebrity voice samples, which they analyzed based on their sound characteristics, such as amplitude, frequency, and entropy. They looked at 20 sound characteristics and identified that all the voices could be segmented into six clusters: ostentatious, colloquial, friendly, authoritative, seductive, and suave. The team then created advertisements for select products using computer generated voices for each of the six clusters, opting for artificial intelligence-created speech instead of celebrity deep fakes due to permission legalities. They chose a shoe and an office chair as their products, and created two different advertisements for each product. One ad was simple, denoting the shoe as comfortable for all-day wear and the office chair as comfortable for sitting in for extended time periods. The other ad was hedonic, denoting the shoe as crafted with Italian leather and the office chair equipped with several massage features. They recorded the four advertisements using both a female and male voice for all six voice clusters. Study participants listened to each of the four advertisements in one of the 12 voices, which was randomly selected. After the advertisement was played, participants were asked if they wanted more information, and later, if they wanted to buy the product (omitting the price as to not add another factor to their decision making). Influencing Consumer Behavior For simple, utilitarian products, they found no significant effect of voice on information seeking behavior. Garg says once participants hear this type of advertisement, they simply decide to purchase or move on. Participants do, however, engage more in information seeking behavior for hedonic products when the voice is ostentatious, seductive, or authoritative. The team also found men were more likely than women to engage with ostentatious or seductive voices, and women were more likely to engage with friendly or colloquial voices. Overall, they found participants did not seek information with male voices. For information seeking, men and women only engage if the voices are female, which is somewhat intuitive. The industry is doing this—Alexa, Google, and Siri all have a female voice. In terms of purchase intention, they found ostentatious voices have higher yields for utilitarian products. Men, especially, were more likely than women to purchase a utilitarian product advertised in an ostentatious voice. Think about advertising a stapler. It’s a stapler—it staples paper—but you advertise it in a French accent to make it sound interesting. Conversely, for hedonic products, an ostentatious voice has a negative effect on purchase intent because Garg says it can make the product sound gimmicky. Their research shows colloquial voices do the best here because people focus more on the advertisement’s content. Across the board, they found seductive voices have a negative effect on purchase intent, but more so on utilitarian products compared to hedonic ones. Men were more likely than women to respond positively to seductive and suave voices. Applying the results Voices are another way smart device companies can personalize their customers’ experiences. Garg says these companies should be aware that there may be a certain voice that will garner the best engagement. Their findings are not isolated to business, but may apply to other industries, such as the media. Garg says, for example, if publications intend to increase reader curiosity and engagement, they should use a female colloquial voice on “click to listen” features. Although not yet tested, Garg says he wouldn’t be surprised if their results extend to real-world settings with real human voices as well. During their research, Garg’s team asked participants if they had heard the advertisement voices before, and about 15 percent of respondents says they had. "These were voices we’d created for the first time,” Garg says. “If they say they’ve heard the voice before, that means they were thinking of them as human voices. Although we didn’t study it that way, I do believe what we’re seeing will be relevant for actual human being’s voices and interactions.” Having researched this for years, Garg says every time he listens to a voice, whether a customer service representative or podcast host, he questions whether or not it is impacting his behavior. A lot of times when I’m making a decision, I know that I’m making that decision passively because of the voice. “I’m acting 50 percent based on the rational information in the voice, but the other 50 percent I just want to listen more. There is an inherent desire for a certain voice.” Garg says his favorite part of the research are those “aha moments,” whether they be the influence of voice in his own life or in the industry—such as large companies using female voices in their products to draw engagement. He says he hopes to continue doing this kind of research to help startups and other companies perform better, as AI-powered voices continue to change the way people interact with technology and consume information. “We’re finding these interesting phenomena that can help create new products that are more effective,” Garg says. “I am trying to increase the economic surplus, in some ways to improve society, and this technology presents numerous opportunities.” Looking to know more? Rajiv Garg from Emory’s Goizueta Business School is available to speak with media – simply click on his icon now to arrange an interview today.
Aston University establishes new independent investment company
Aston University is part of a group of eight universities which has established a new investment company Midlands Mindforge will accelerate the commercialisation of university research It aims to raise up to £250 million from investors. Aston University is one of eight research intensive universities in the Midlands to establish a new investment company to accelerate the commercialisation of university spinouts and early-stage IP rich businesses in the region. Midlands Mindforge Limited has been co-founded by Aston University, University of Birmingham, Cranfield University, Keele University, University of Leicester, Loughborough University, University of Nottingham and University of Warwick, collectively Midlands Innovation. This ambitious, patent capital investment company plans to raise up to £250 million from strategic corporate partners, institutional investors and qualifying individuals. It aims to transform ground-breaking science and technology into successful businesses with real-world impact. Midlands Mindforge will help to address the significant funding deficit for early-stage technology businesses in the region. Through the combination of additional capital and company-building skills, Midlands Mindforge will lay the foundations of a more vibrant ecosystem for emerging science-backed companies in areas such as Clean Technology, AI and Computational Science, Life Sciences and Health Tech. Professor Aleks Subic, Vice-Chancellor of Aston University, said: "Aston University has a strong track record in bringing together industry and academia to solve real world problems and drive innovation through applied and translational research. Â Investment raised through Midlands Mindforge will enable a step change that will ensure we get the very best outcomes for our research. "The impact of increased investment in research translation will be felt widely, with Midlands Mindforge supporting the growth of high value added businesses and jobs in the region and creating the right conditions to build future global companies. This is a hugely exciting time for Aston University and the wider Midlands Innovation group of universities, and I look forward to seeing the benefits that this strategic development will bring." Collectively, the eight founding universities have the most postgraduate students, the highest levels of annual income, more research disclosures and patents generated per unit of research spend in the last three years, in comparison to any other UK university grouping. Minister of State for Science, Research & Innovation George Freeman MP said: "Commercialising UK science & technology for global industrial adoption has never been more urgent for both the UK economy and the global resource challenges facing us. The Midlands Innovation universities are driving a new era of innovation from robotics and advanced manufacturing to life science and autonomous vehicles and much more. "As we in Government increase UK public R&D to a record £20 billion a year, the key is private finance backing spinouts and scale-ups. The Midlands is rapidly becoming a world class UK cluster of excellence and Midlands Mindforge will play a key role in bringing global investors to help back world class companies." Chairman of the Midlands Engine Partnership, Sir John Peace, said: "The Midlands has always been associated with exceptional invention and creativity, but has long experienced significant underinvestment and consequently productivity levels have lagged behind the rest of the UK. "This bold and ambitious initiative led by the Midlands Innovation universities has the potential to help close the investment gap, supporting our region to reach its true potential for sustainable economic growth. Midlands Mindforge will help to further fast-track commercialisation of research ideas, creating a more resilient economy and playing an important role in levelling up the Midlands." Andy Street, Mayor of the West Midlands, said: "A key part of my mayoral mission is to drive our regional recovery forward and help generate the high-quality jobs of the future in order to improve quality of life for local people. This exciting new investment vehicle will very much support that mission planting the seeds for long-term sustainable economic growth here in the West Midlands. "Many brilliant ideas and top businesses have spun out from Midlands universities and this new venture will help us to advance that agenda and retain more of our innovative success stories within our region. "Together we can better nurture the enterprising talent on our doorstep and this new endeavour creates a wonderful opportunity to do just that." For more information about Midlands Mindforge visit www.midlandsmindforge.com
Ask an Expert: Is the "AI Moratorium" too far reaching?
Recent responses to chatGPT have featured eminent technologists calling for a six-month moratorium on the development of “AI systems more powerful than GPT-4.” Dr. Jeremy Kedziora, PieperPower Endowed Chair in Artificial Intelligence at Milwaukee School of Engineering, supports a middle ground approach between unregulated development and a pause. He says, "I do not agree with a moratorium, but I would call for government action to develop regulatory guidelines for AI use, particularly for endowing AIs with actions." Dr. Kedziora is available as a subject matter expert on the recent "AI moratorium" that was issued by tech leaders. According to Dr. Kedziora: There are good reasons to call for additional oversight of AI creation: Large deep or reinforcement learning systems encode complicated relationships that are difficult for users to predict and understand. Integrating them into daily use by billions of people implies some sort of complex adaptive system in which it is even more difficult for planners to anticipate, predict, and plan. This is likely fertile ground for unintended – and bad – outcomes. Rather than outright replacement, a very real possibility is that AI-enabled workers will have sufficiently high productivity that we’ll need less workers to accomplish tasks. The implication is that there won’t be enough jobs for those who want them. This means that governments will need to seriously consider proposals for UBI and work to limit economic displacement, work which will require time and political bargaining. I do not think it is controversial that we would not want a research group at MIT or CalTech, or anywhere developing an unregulated nuclear weapon. Given the difficulty in predicting its impact, AI may well be in the same category of powerful, suggesting that its creation should be subject to the democratic process. At the same time, there are some important things to keep in mind regarding chatGPT-like AI systems that suggest there are inherent limits to their impact: Though chatGPT may appear–at times–to pass the famous Turing test, this does not imply these systems ’think,’ or are ’self-aware,’ or are ’alive.’ The Turing test aims to avoid answering these questions altogether by simply asking if a machine can be distinguished from a human by another human. At the end of the day, chatGPT is nothing more than a bunch of weights! Contemporary AIs–chatGPT included–have very limited levers to pull. They simply can’t take many actions. Indeed, chatGPT’s only action is to create text in response to a prompt. It cannot do anything independently. Its effects, for now, are limited to passing through the hands of humans and to the social changes it could thereby create. The call for a moratorium emphasizes ‘control’ over AI. It is worth asking just what this control means. Take chatGPT as an example–can its makers control responses to prompts? Probably only in a limited fashion at best, with less and less ability as more people use it. There simply aren’t resources to police its responses. Can chatGPT’s makers ‘flip the off switch?’ Absolutely – restricting access to the API would effectively turn chatGPT off. In that sense, it is certainly under the same kind of control humans subjected to government are. Keep in mind that there are coordination problems – just because there is an AI moratorium in the US does not mean that other countries–particularly US adversaries– will stop development. And as others have said: “as long as AI systems have objectives set by humans, most ethics concerns related to artificial intelligence come from the ethics of the countries wielding them.” There are definitional problems with this sort of moratorium – who would be subject to it? Industry actors? Academics? The criterion those who call for the moratorium use is “AI systems more powerful than GPT-4.” What does “powerful” mean? Enforcement requires drawing boundaries around which AI development is subject to a moratorium – without those boundaries how would such a policy be enforced? It might already be too late – some already claim that they’ve recreated chatGPT. There are two major groups to think about when looking for develop regulatory solutions for AI: academia and industry. There may already be good vehicles for regulating academic research, for example oversight of grant funding. Oversight of AI development in industry is an area that requires attention and application of expertise. If you're a journalist covering Artificial Intelligence, then let us help. Dr. Kedziora is a respected expert in Data Science, Machine Learning, Statistical Modeling, Bayesian Inference, Game Theory and things AI. He's available to speak with the media - simply click on the icon now to arrange an interview today.
Aston University and asbestos consultancy to use AI to improve social housing maintenance
• Aston University and Thames Laboratories enter 30-month Knowledge Transfer Partnership • Will use machine-learning and AI to create a maintenance prioritisation system • Collaboration will reduce costs, emissions, enhance productivity and improve residents' satisfaction. Aston University is teaming up with asbestos consultancy, Thames Laboratories (TL) to improve efficiency of social housing repairs. There are over 1,600 registered social housing providers in England, managing in excess of 4.4 million homes. Each of these properties requires statutory inspections to check gas, asbestos and water hygiene, in addition to general upkeep. However, there is not currently a scheduling system available that offers integration between key maintenance and safety contractors, resulting in additional site visits and increased travel costs and re-work. Aston University computer scientists will use machine-learning and AI to create a maintenance prioritisation system that will centralise job requests and automatically allocate them to the relevant contractors. The collaboration is through a Knowledge Transfer Partnership (KTP) - a collaboration between a business, an academic partner and a highly-qualified researcher, known as a KTP associate. This partnership builds on the outcomes of TL’s first collaboration with Aston University, by expanding the system developed for the company’s in-house use - which directs its field staff to jobs. The project team will improve the system developed during the current KTP to enable it to interact with client and contractor systems, by combining an input data processing unit, enhanced optimisation algorithms, customer enhancements and third-party add-ons into a single dynamic system. The Aston University team will be led by Aniko Ekart, professor of artificial intelligence. She said: “It is a privilege to be involved in the creation of this system, which will select the best contractor for each job based on their skill set, availability and location and be reactive to changing priorities of jobs." TL, based in Fenstanton, just outside Cambridge, provides asbestos consultancy, project management and training to businesses, local authorities, social housing and education facilities, using a fleet of mobile engineers across the UK. John Richards, managing director at Thames Laboratories, said: “This partnership will allow us to adopt the latest research and expertise from a world-leading academic institute to develop an original solution to improving the efficiency of social housing repairs, maintenance and improvements to better meet the needs of social housing residents.” Professor Ekart will be joined by Dr Alina Patelli as academic supervisor. Dr Patelli brings experience of software development in the commercial sector as well as expertise in applying optimisation techniques with focus on urban systems. She said: “This is a great opportunity to enhance state-of-the-art optimisation and machine learning in order to fit the needs of the commercial sector and deliver meaningful impact to Thames Laboratories.”
Cyber threats have become one of the leading issues for corporations, governments, and public institutions across America. With ransomware attacks, hackers, and other nefarious threats, the issue is becoming a daily occurrence and leading news story. Rensselaer Polytechnic Institute’s James Hendler, director of the Future of Computing Institute, Tetherless World Professor of Computer, Web, and Cognitive Sciences, and director of the RPI-IBM Artificial Intelligence Research Collaboration, weighs in on what we should all know about cybersecurity. Overview Think about cybersecurity the way you think about home security – the more valuables you have, the more security you need. A normal user needs the equivalent of a lock on the door, which most of our computers provide out of the box. However, a user with a fair amount of personal information, who keeps financial records or runs a small business, probably wants a firewall or other additional protection. We used to tell people to protect their computers with firewalls, malware detectors, and the like, but now it is much more important to protect your web access, be wary of external sites, and keep your passwords secure and not easily guessed. Use of a password manager program can be really helpful for people who use a lot of different accounts. Threats The biggest threat facing individuals is identity theft caused by someone getting into an account that you don’t control. Most malware or password stealing comes via a phishing attack (a fake email that convinces you to click a bad link), so if you see an offer that looks too good to be true, don’t believe it. Never give out a password or personal information without confirming that it is legitimate. We also recommend not using major accounts (like Google, Facebook, etc.) to log in to new apps where you aren’t completely sure of the reliability – you’re safer if you use a separate password. It’s also worth noting that these kinds of attacks are now happening on cell phones – if you get a text saying your Amazon, Netflix, or other services have been shut off, be very careful. These companies almost never send out such messages, and if they do, they come via email, not text. For businesses, ransomware is becoming an increasing challenge. Frequent backups and dual authentication are absolute musts for small businesses. Large businesses, and especially those with cyber-physical connections such as a manufacturing device, must have someone on the team who understands internet technology. Outside audits done annually, at least, are also highly recommended. The biggest danger in cybersecurity is that people, especially in businesses, think that the software industry will fix things and that they don’t have to worry. That’s like expecting auto manufacturers to stop car theft, or the government to prevent all crime – these organizations certainly need to help, but they cannot be perfect. So while there definitely needs to be a role for manufacturers and government, people need to understand that the threats are now coming from social interactions such as phishing, or serious criminal enterprises such as ransomware attackers, and not just maladjusted teenagers. They must be ready to pay for some security if they have things on their network that need protection. The Cloud Cloud-based services are a major boon to cybersecurity for individuals and small businesses if, and only if, people protect their access. If a breach is reported to you by a company, don’t ignore it, change your password, and, whenever possible, use dual authentication. The cloud companies can afford to spend more on security than you can and thus your information stored in these services tends to be quite secure. However, people need to be careful in using the cloud. Just as you may trust a bank with your money, you want to be sure not to be robbed on your way there. Future Computing Systems and Cybersecurity New technologies, such as artificial intelligence (AI), are arising all the time in today’s fast-moving cyber world. As these technologies arise, they can create new opportunities for cybersecurity, but can also create new challenges. Cybercrime will never disappear, and each new capability comes with a price. Increased education and awareness of emerging computing technologies (blockchain, quantum, etc.) are important not just for the expert, but also for the general public. It is important to stay informed and pay attention to what is being reported. Just as buying a new appliance can be a great advantage at home (I love my new air-fryer), you also have to be sure to be using it appropriately (used wrong, it can cause fires). Looking to learn more or connect with an expert for your questions and coverage? James Hendler is the director of the Rensselaer Future of Computing Institute, Tetherless World Professor of Computer, Web, and Cognitive Sciences, and director of the RPI-IBM Artificial Intelligence Research Collaboration. Hendler has authored over 400 books, technical papers, and articles in the areas of Semantic Web, artificial intelligence, cybersecurity, and high-performance processing. Hendler is available to speak with media - simply click on his icon now to arrange an interview today.
AI-powered cruise control system may pave the way to fuel efficiency and traffic relief
The CIRCLES Consortium, consisting of Vanderbilt University, UC Berkeley, Temple University and Rutgers University-Camden, in coordination with Nissan North America and the Tennessee Department of Transportation, concluded a five-day open-track experiment on Nov. 18. Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing (CIRCLES) Researchers tested an AI-powered cruise control system designed to increase fuel savings and ease traffic using 100 specially equipped Nissan Rogue vehicles. The experiment—which ran from Nov. 14 through Nov. 18 on a sensor-filled portion of Interstate 24—is based on the results from an earlier, closed-track study where a single smart vehicle smoothed human-caused traffic congestion, leading to significant fuel savings. A single AI-equipped vehicle could influence the speed and driving behavior of up to 20 surrounding cars, causing a kind of positive ripple effect in day-to-day traffic. The CIRCLES Consortium will spend the next several months analyzing data collected on the AI-equipped vehicles and their impact on the flow of traffic over the duration of the experiment. The test was conducted on the recently opened I-24 MOTION testbed, the only real-world automotive testing environment of its kind in the world. Stretching for four miles just southeast of downtown Nashville, the smart highway is equipped with 300 4K digital sensors capable of logging 260,000,000 vehicle-miles of data per year. The CIRCLES Consortium research is supported by the National Science Foundation and the U.S. Departments of Transportation and Energy. Support was also provided by Toyota North America and General Motors. The experiment included Toyota RAV4 and Cadillac XT5 vehicles. Preliminary vehicle and traffic flow detection in the I-24 Mobility Technology Interstate Observation Network (MOTION). “On November 16 alone, the system recorded a total of 143,010 miles driven and 3,780 hours of driving. The I-24 MOTION system, combined with vehicle energy models developed in the CIRCLES project, provided an estimation of the fuel consumption of the whole traffic flow during those hours. The concept we are hoping to demonstrate is that by leveraging this new traffic system to collect data and estimate traffic and applying artificial intelligence technology to existing cruise control systems, we can ease traffic jams and improve fuel economy,” the CIRCLES team said in a joint statement. “Nissan has always been a pioneer in automotive innovation, and with our long-term vision, Nissan Ambition 2030, we know our future is autonomous, connected and electric,” said Liam Pedersen, deputy general manager at the Nissan Alliance Innovation Lab in California’s Silicon Valley. “CIRCLES shares our common goal of building a safer, cleaner world by empowering mobility.” “When it comes to transportation and mobility in Tennessee, we are at a critical juncture,” said Deputy Governor and TDOT Commissioner Butch Eley. “Traffic congestion is now becoming more prominent throughout Tennessee, and not just in urban areas. Addressing these challenges will force us to think critically about solutions, as transportation infrastructure projects traditionally are not identified nor completed before traffic congestion more dramatically affects our quality of life. One of these solutions is greater use of technology to enhance mobility. We are confident that this project and others like it will further strengthen Tennessee’s reputation for being a hub of automotive excellence.” “The I-24 MOTION project is a first-of-its-kind testbed, where we’ll be able to study in real time the impact connected and autonomous vehicles have on traffic in an open road setting,” said Meredith Cebelak, adjunct instructor in civil and environmental engineering at Vanderbilt and Tennessee transportation and transportation systems management and operations department leader at Gresham Smith. “The permanent infrastructure has been designed and installed, meaning the testbed will always be ‘on’ and available to researchers. By unlocking a new understanding of how these vehicles influence traffic, vehicle, infrastructure, and traffic management strategies, design can be optimized to reduce traffic concerns in the future to improve safety, air quality and fuel efficiency.” “Partnership across universities, government and the private sector is the key to pioneering projects like this one,” Vice Provost for Research and Innovation Padma Raghavan said. “From its earliest inception, all the partners in this effort have played vital roles. That trusted collaboration continues as the team analyzes results to seek new insights to address pressing challenges in transportation in Tennessee and beyond.”
Public lecture: how can we have a good future with artificial intelligence?
Public lecture: how can we have a good future with artificial intelligence?AI expert and educator Professor Anikó Ekárt to discuss one of today’s most provocative topics Lecture will take place on 28 February at Aston University Talk to explore artificial intelligence’s capabilities, benefits and pitfalls. The potential impact of artificial intelligence (AI) on our daily lives will be explored in a public lecture at Aston University. The University is inviting the public onto its campus on Tuesday 28 February to hear Professor Anikó Ekárt discuss one of today’s most provocative topics. Research into AI began in the1950s and since then it has played an increasing role in daily lives, such as chatbots and digital assistants. As an AI researcher and educator, Professor Ekárt will take a pragmatic view of the technology, arguing that society will benefit from it – but only if it is used responsibly. She said: “Digital assistants based on speech recognition are now broadly accepted and successfully embedded in many business services. “However, the most recent release of a chatbot with amazing writing capabilities has divided the world; some are relieved that their job may now become substantially easier, but others have questioned the impact of this on education. “In the lecture, I’ll suggest three key directions; responsible use of AI, exploring many AI techniques rather than focusing on just one, and educating the public about AI’s capabilities, benefits and pitfalls.” She will illustrate the success and further potential of less well-known AI techniques, such as evolutionary computation, genetic programming and symbolic regression, based on her 25 years of research. Anikó who is a professor of artificial intelligence, joined Aston University in 2006 as a lecturer. She leads the artificial intelligence research theme within the School of Informatics and Digital Engineering. Her research interests are centred around AI methods and their application, focusing on evolutionary algorithms and genetic programming. She has successfully contributed to applications of AI techniques to health, engineering, transport, and art. In 2022 she was the winner of the Evo* Award for Outstanding Contribution to Evolutionary Computation in Europe. The free event will be taking place on 28 February from 6 pm to 8 pm and will be followed by a drinks reception. To sign up for a place visit https://www.eventbrite.co.uk/e/an-inaugural-lecture-by-professor-aniko-ekart-tickets-516518760517
AI-Generated Content is a Game Changer for Marketers, but at What Cost?
Goizueta’s David Schweidel pitted man against the machine to create SEO web content only to find that providing an editor with bot-generated content trounces the human copywriter every time. Good news for companies looking to boost productivity and save cash, he says. But could there be other hidden costs? In December 2022, The New York Times ran a piece looking back on the year’s biggest consumer tech updates. The review was mixed. Ownership shifts in the world of social media garnered special mentions, but hardware innovations had been largely “meh,’ mused the Times. There was one breakthrough area that warranted attention, however: AI-powered language-processing tech capable of generating natural-looking text, the same technology that powers familiar chatbots. And one such technology could well be poised to “invade our lives in 2023.” Earlier in December, AI research lab OpenAI, released the latest update to its Generative Pre-Trained Transformer technology, an open source artificial intelligence. It’s latest iteration, ChatGPT, immediately went viral. Here was an AI assistant that sounded intelligent. Not only could it answer any question thrown its way without supervised training, but when prompted, it could also write blog posts, as well as find and fix bugs in programming code. ChatGPT could draft business proposals and even tell jokes. All of this at a speed that beggared belief. Since its first release in 2020, OpenAI’s GPT technology has powered through a slew of updates that have seen its capabilities leap forward “by light years” in less than 24 months, says Goizueta Professor of Marketing, David Schweidel. For businesses looking to harness this rapidly-evolving technology, the potential is clearly enormous. But aren’t there also risks that industry and consumers alike will need to navigate? Schweidel is clear that the academic community and initiatives such as the Emory AI Humanity Initiative have a critical role in asking hard questions—and in determining the limitations and dangers, as well as the opportunities, inherent in tech innovation—because, as he puts it, “these things are going to happen whether we like it or not.” Man Versus Machine To that end, Schweidel and colleagues from Vienna University of Economics and Business and the Modul University of Vienna have put together a study looking at how well natural language generation technologies perform in one specific area of marketing: drafting bespoke content for website search engine optimization, better known as SEO. What they find is that content crafted by the machine, after light human editing, systematically outperforms its human counterparts—and by a staggering margin. Digging through the results, Schweidel and his colleagues can actually pinpoint an almost 80 percent success rate for appearing on the first page of search engine results with AI-generated content. This compares with just 22 perfect of content created by human SEO experts. In other words, the AI content passed to a human is roughly four times more effective than a skilled copywriter working alone. Reaching these findings meant running two real-time, real-world experiments, says Schweidel. First, he and his colleagues had to program the machine, in this case GPT 2, an earlier incarnation of GPT. GPT relies on natural language generation (NGL), a software process that converts manually uploaded input into authentic-sounding text or content—comparable in some ways to the human process of translating ideas into speech or writing. To prepare GPT-2 for SEO-specific content creation, Schweidel et al. started with the pre-trained GPT-2, and then let the machine do the heavy lifting: searching the internet for appropriate results based on the desired keyword, scraping the text of the websites, and updating GPT-2 to “learn” what SEO looks like, says Schweidel. We partnered with an IT firm and a university to run our field experiments. This meant creating SEO content for their websites using GPT-2 and actual human SEO experts, and then doing A/B testing to see which content was more successful in terms of landing in the top 10 search engine results on Google. So this was an opportunity to put the AI bot to the test in a real-world setting to see how it would perform against people. The results point to one clear winner. Not only did content from GPT-2 outperform its human rivals in SEO capabilities, it did so at scale. The AI-generated content scored a daily median result of seven or more hits in the first page of Google search results. The human-written copy didn’t make it onto the first result page at all. On its best day, GPT showed up for 15 of its 19 pages of search terms inside the top 10 search engine results page, compared with just two of the nine pages created by the human copywriters—a success rate of just under 80 percent compared to 22 percent. Savings at Scale The machine-generated content, after being edited by a human, trounces the human in SEO. But that’s not all, says Schweidel. The GPT bot was also able to produce content in a fraction of the time taken by the writers, reducing production time and associated labor costs by more than 90 percent, he says. “In our experiments, the copywriters took around four hours to write a page, while the GPT bot and human editor took 30 minutes. Now assuming the average copywriter makes an annual $45K on the basis of 1,567 hours of work, we calculate that the company we partnered with would stand to save more than $100,000 over a five-year period just by using the AI bot in conjunction with a human editor, rather than relying on SEO experts to craft content. That’s a 91 percent drop in the average cost of creating SEO content. It’s an orders of magnitude difference in productivity and costs.” But there are caveats. First off, there’s the quality of the machine-generated content to consider. For all its mind-boggling capabilities, even the newly released ChatGPT tends to read somewhat sterile, says Schweidel. That’s a problem both in terms of Google guidelines and brand coherence. Human editors are still needed in order to attenuate copy that can sound a little “mechanical.” “Google is pretty clear in its guidelines: Content generated by machines alone is a definite no-no. You also need to factor in the uncanny valley effect whereby something not quite human can come off as weird. Having an editor come in to smooth out AI content is critical to brand voice as well as the human touch.” Asking the Big Questions Then there are the moral and metaphysical dimensions of machine learning and creativity that beg an important question: Just because we can, does that mean we should? Here, Schweidel has grave reservations about the future of ChatGPT and its ilk. The potential of this kind of technology is extraordinarily exciting when you think about the challenges we face from productivity to pandemics, from sustainable growth to climate change. But let’s be very clear about the risks, too. AI is already capable of creating content—audio, visual and written—that looks and feels authentic. In a world that is hugely polarized, you have to ask yourself: How can that be weaponized? At the end of the day, says Schweidel, the large language models powering these generative AIs are essentially “stochastic parrots:” trained mimics whose output can be hard to predict. In the wrong hands, he warns, the potential for misinformation—and worse—could well be “terrifying.” “Shiny new tech is neither inherently good nor bad. It’s human nature to push the boundaries. But we need to ensure that the guardrails are in place to regulate innovation at this kind of pace, and that’s not easy. Governments typically lag far behind OpenAI and companies like them, even academics have a hard time keeping up. The real challenge ahead of us will be about innovating the guardrails in tandem with the tech—innovating our responsible practices and processes. Without effective safeguards in place, we’re on a path to potential destruction.” Covering AI or interesting in knowing more about this fascinating topic - then let our experts help with your coverage and stories. David Schweidel is the Rebecca Cheney McGreevy Endowed Chair and Professor of Marketing at Emory University's Goizueta Business School. Simply click on David's icon now to arrange an interview today.
Aston University AI expertise helps estimate daily transmission rates of infections such as Covid
Model used antibody data collected at blood donation centres Data obtained allowed academics to estimate the proportion of people who were going undiagnosed Current epidemiological models tend not to be as effective at estimating hidden variables such as daily infection rates. Aston University researchers have helped develop a mathematical model which can estimate daily transmission rates of infections such as Covid by testing for antibodies in blood collected at blood donation centres. Current epidemiological models that are usually used tend not to be as effective at adjusting quickly to changes in infection levels. Working with researchers at the Universidade Federal de Minas Gerais in Brazil they conducted a large longitudinal study applying a compartmental model, which is a general modelling technique often applied to the mathematical modelling of infectious diseases, to results obtained from Brazilian blood donor centres. The testing was done by Fundacao Hemominas, one of the largest blood services in Brazil, which covers an area similar to that of continental France. They used the reported number of SARS-CoV-2 cases along with serology results (diagnostic methods used to identify antibodies and antigens in patients’ samples) from blood donors as inputs and delivered estimates of hidden variables, such as daily values of transmission rates and cumulative incidence rate of reported and unreported cases. The model discussed in the paper SARS-CoV-2 IgG Seroprevalence among Blood Donors as a Monitor of the COVID-19 Epidemic, Brazil gave the experts the ability to have a more refined view of the infection rates and relative rate of immunity compared to official measurements. The testing started at the beginning of the pandemic and involved 7,837 blood donors in seven cities in Minas Gerais, Brazil during March–December 2020. At that point testing wasn’t widely available and there was a high proportion of undetected asymptomatic or light symptomatic cases. The data obtained allowed the experts to estimate the proportion of people who were going undiagnosed. Dr Felipe Campelo, senior lecturer in computer science at Aston University, said: “Public communication about the COVID-19 epidemic was based on officially reported cases in the community, which strongly underestimates the actual spread of the disease in the absence of widespread testing. “This difference underscores the convenience of using a model-based approach such as the one we proposed, because it enables the use of measured data for estimating variables such as the total number of infected persons. “Our model delivers daily estimates of relevant variables that usually stay hidden, including the transmission rate and the cumulative number of reported and unreported cases of infection.” In Brazil in July 2020 there was a sharp increase in the number of people tested as new infrastructure became available, which allowed the experts to further validate their methodology by observing how officially recorded data became closer to the model predictions once testing became more widespread, including for asymptomatic or mildly symptomatic people. They applied the model to antibodies found in blood given by donors and used it to estimate the proportion of undiagnosed cases, and to analyse changes in the infection rate, that is, how many people each case infected on average. Previously this has been viewed as a fixed value or a fixed value over a long duration of time, but the dynamics of the spread of Covid change much faster than that. This aspect was very important in early days of the pandemic and could also be applied to similar diseases. Looking forward, the experts aim to improve the accuracy of the model by introducing changes to account for vaccination effects, waning immunity and the potential emergence of new variants. The paper SARS-CoV-2 IgG Seroprevalence among Blood Donors as a Monitor of the COVID-19 Epidemic, Brazil has been published in Volume 28, Number 4—April 2022 of Emerging Infectious Diseases.