Diffbot, a Stanford startup, is building an AI-based spider that reads as many pages as possible on the entire public web, and extracts as many facts from those pages as it can. “Like GPT-3, Diffbot’s system learns by vacuuming up vast amounts of human-written text found online. But instead of using that data to train a language model, Diffbot turns what it reads into a series of three-part factoids that relate one thing to another: subject, verb, object.” (MIT Technology Review, 4 September 2020) Knowledge graphs – which is what this is all about – have been around for a long time. However, they have been created mostly manually or only with regard to certain areas. Some years ago, Google started using knowledge graphs too. Instead of giving us a list of links to pages about Spider-Man, the service gives us a set of facts about him drawn from its knowledge graph. But it only does this for its most popular search terms. According to MIT Technology Review, the startup wants to do it for everything. “By fully automating the construction process, Diffbot has been able to build what may be the largest knowledge graph ever.” (MIT Technology Review, 4 September 2020) Diffbot’s AI-based spider reads the web as we read it and sees the same facts that we see. Even if it does not really understand what it sees – we will be amazed at the results.
IBM will stop developing or selling facial recognition software due to concerns the technology is used to support racism. This was reported by MIT Technology Review on 9 June 2020. In a letter to Congress, IBM’s CEO Arvind Krishna wrote: “IBM firmly opposes and will not condone uses of any technology, including facial recognition technology offered by other vendors, for mass surveillance, racial profiling, violations of basic human rights and freedoms, or any purpose which is not consistent with our values and Principles of Trust and Transparency. We believe now is the time to begin a national dialogue on whether and how facial recognition technology should be employed by domestic law enforcement agencies.” (Letter to Congress, 8 June 2020) The extraordinary letter “also called for new federal rules to crack down on police misconduct, and more training and education for in-demand skills to improve economic opportunities for people of color” (MIT Technology Review, 9 June 2020). A talk at Stanford University in 2018 warned against the return of physiognomy in connection with face recognition. The paper is available here.
According to Gizmodo, a robot from Boston Dynamics has been deployed to a park in Singapore to remind people they should follow social distancing guidelines during the pandemic. Spot is not designed as a security robot, like the K5 or the K3 from Knightscope. But it has other qualities: it can walk on four legs and is very fast. The machine, which was set loose on 8 May 2020 in Bishan-Ang Mo Kio Park, “broadcasts a message reminding visitors they need to stay away from other humans, as covid-19 poses a very serious threat to our health”. It “was made available for purchase by businesses and governments last year and has specially designed cameras to make sure it doesn’t run into things.” (Gizmodo, 8 May 2020) According to a press release from Singapore’s GovTech agency, the cameras will not be able to track or recognize specific individuals, “and no personal data will be collected” (Gizmodo, 8 May 2020). COVID-19 demonstrates that digitization and technologization can be helpful in crises and disasters. Service robots such as security robots, transport robots, care robots and disinfection robots are in increasing demand.
Artificial intelligence is underestimated in some aspects, but overestimated in many. It is currently seen as a secret weapon against COVID-19. But it most probably is not. The statement of Alex Engler, a David M. Rubenstein Fellow, is clear: “Although corporate press releases and some media coverage sing its praises, AI will play only a marginal role in our fight against Covid-19. While there are undoubtedly ways in which it will be helpful – and even more so in future pandemics – at the current moment, technologies like data reporting, telemedicine, and conventional diagnostic tools are far more impactful.” (Wired, 26 April 2020) Above all, however, it is social distancing that interrupts the transmission paths and thus curbs the spread of the virus. And it’s drugs that will solve the problem this year or next. So there is a need for behavioural adjustment and medical research. Artificial intelligence is not really needed. Alex Engler identified the necessary heuristics for a healthy skepticism of AI claims around Covid-19 and explained them in Wired magazine.
The paper “Co-Robots as Care Robots” by Oliver Bendel, Alina Gasser and Joel Siebenmann, accepted at the AAAI 2020 Spring Symposium “Applied AI in Healthcare: Safety, Community, and the Environment”, can be accessed via arxiv.org/abs/2004.04374. From the abstract: “Cooperation and collaboration robots, co-robots or cobots for short, are an integral part of factories. For example, they work closely with the fitters in the automotive sector, and everyone does what they do best. However, the novel robots are not only relevant in production and logistics, but also in the service sector, especially where proximity between them and the users is desired or unavoidable. For decades, individual solutions of a very different kind have been developed in care. Now experts are increasingly relying on co-robots and teaching them the special tasks that are involved in care or therapy. This article presents the advantages, but also the disadvantages of co-robots in care and support, and provides information with regard to human-robot interaction and communication. The article is based on a model that has already been tested in various nursing and retirement homes, namely Lio from F&P Robotics, and uses results from accompanying studies. The authors can show that co-robots are ideal for care and support in many ways. Of course, it is also important to consider a few points in order to guarantee functionality and acceptance.” Due to the outbreak of the COVID-19 pandemic, the physical meeting to be held at Stanford University was postponed. It will take place in November 2020 in Washington (AAAI 2020 Fall Symposium Series).
The Centers for Disease Control and Prevention of the United States Department of Health and Human Services have launched a chatbot that will help people decide what to do if they have potential Coronavirus symptoms such as fever, cough, or shortness of breath. This was reported by the magazine MIT Technology Review on 24 March 2020. “The hope is the self-checker bot will act as a form of triage for increasingly strained health-care services.” (MIT Technology Review, 24 March 2020) According to the magazine, the chatbot asks users questions about their age, gender, and location, and about any symptoms they’re experiencing. It also inquires whether they may have met someone diagnosed with COVID-19. On the basis of the users’ replies, it recommends the best next step. “The bot is not supposed to replace assessment by a doctor and isn’t intended to be used for diagnosis or treatment purposes, but it could help figure out who most urgently needs medical attention and relieve some of the pressure on hospitals.” (MIT Technology Review, 24 March 2020) The service is intended for people who are currently located in the US. International research is being done not only on useful but also on moral chatbots.
The company Neon picks up an old concept with its Neons, namely that of avatars. Twenty years ago, Oliver Bendel distinguished between two different types in the Lexikon der Wirtschaftsinformatik. With reference to the second, he wrote: “Avatars, on the other hand, can represent any figure with certain functions. Such avatars appear on the Internet – for example as customer advisors and newsreaders – or populate the adventure worlds of computer games as game partners and opponents. They often have an anthropomorphic appearance and independent behaviour or even real characters …” (Lexikon der Wirtschaftsinformatik, 2001, own translation) It is precisely this type that the company, which is part of the Samsung Group and was founded by Pranav Mistry, is now adapting, taking advantage of today’s possibilities. “These are virtual figures that are generated entirely on the computer and are supposed to react autonomously in real time; Mistry spoke of a latency of less than 20 milliseconds.” (Heise Online, 8 January 2019, own translation) The neons are supposed to show emotions (as do some social robots that are conquering the market) and thus facilitate and strengthen bonds. “The AI-driven character is neither a language assistant a la Bixby nor an interface to the Internet. Instead, it is a friend who can speak several languages, learn new skills and connect to other services, Mistry explained at CES.” (Heise Online, 8 January 2019, own translation)
In 2018, Dr. Yuefang Zhou and Prof. Dr. Martin Fischer initiated the first international workshop on intimate human-robot relations at the University of Potsdam, “which resulted in the publication of an edited book on developments in human-robot intimate relationships”. This year, Prof. Dr. Martin Fischer, Prof. Dr. Rebecca Lazarides, and Dr. Yuefang Zhou are organizing the second edition. “As interest in the topic of humanoid AI continues to grow, the scope of the workshop has widened. During this year’s workshop, international experts from a variety of different disciplines will share their insights on motivational, social and cognitive aspects of learning, with a focus on humanoid intelligent tutoring systems and social learning companions/robots.” (Website Embracing AI) The international workshop “Learning from Humanoid AI: Motivational, Social & Cognitive Perspectives” will take place on 29 and 30 November 2019 at the University of Potsdam. Keynote speakers are Prof. Dr. Tony Belpaeme, Prof. Dr. Oliver Bendel, Prof. Dr. Angelo Cangelosi, Dr. Gabriella Cortellessa, Dr. Kate Devlin, Prof. Dr. Verena Hafner, Dr. Nicolas Spatola, Dr. Jessica Szczuka, and Prof. Dr. Agnieszka Wykowska. Further information is available at embracingai.wordpress.com/.
Artificial intelligence is spreading into more and more application areas. American scientists have now developed a system that can supplement texts: “Talk to Transformer”. The user enters a few sentences – and the AI system adds further passages. “The system is based on a method called DeepQA, which is based on the observation of patterns in the data. This method has its limitations, however, and the system is only effective for data on the order of 2 million words, according to a recent news article. For instance, researchers say that the system cannot cope with the large amounts of data from an academic paper. Researchers have also been unable to use this method to augment texts from academic sources. As a result, DeepQA will have limited application, according to the researchers. The scientists also note that there are more applications available in the field of text augmentation, such as automatic transcription, the ability to translate text from one language to another and to translate text into other languages.” The sentences in quotation marks are not from the author of this blog. They were written by the AI system itself. You can try it via talktotransformer.com.
Some months ago, researchers at the University of Massachusetts showed the climate toll of machine learning, especially deep learning. Training Google’s BERT, with its 340 million data parameters, emitted nearly as much carbon as a round-trip flight between the East and West coasts. According to Technology Review, the trend could also accelerate the concentration of AI research into the hands of a few big tech companies. “Under-resourced labs in academia or countries with fewer resources simply don’t have the means to use or develop such computationally expensive models.” (Technology Review, 4 October 2019) In response, some researchers are focused on shrinking the size of existing models without losing their capabilities. The magazine wrote enthusiastically: “Honey, I shrunk the AI” (Technology Review, 4 October 2019) There are advantages not only with regard to the environment and to the access to state-of-the-art AI. According to Technology Review, tiny models will help bring the latest AI advancements to consumer devices. “They avoid the need to send consumer data to the cloud, which improves both speed and privacy. For natural-language models specifically, more powerful text prediction and language generation could improve myriad applications like autocomplete on your phone and voice assistants like Alexa and Google Assistant.” (Technology Review, 4 October 2019)