“The goal of ALOE is to develop new artificial intelligence theories and techniques to make online education for adults at least as effective as in-person education in STEM fields,” says Co-PI Ashok Goel, Professor of Computer Science and Human-Centered Computing and the Chief Scientist with the Center for 21stCentury Universities at Georgia Tech
Research and development at ALOE aims to blend online educational resources and courses to make education more widely available, as well as use virtual assistants to make it more affordable and achievable. According to Goel, ALOE will make fundamental advances in personalization at scale, machine teaching, mutual theory of mind and responsible AI.
The ALOE Institute represents a powerful consortium of several universities (Arizona State, Drexel, Georgia Tech, Georgia State, Harvard, UNC-Greensboro); technical colleges in TCSG; major industrial partners (Boeing, IBM and Wiley); and non-profit organizations (GRA and IMS).
AI is being used to monitor students and their work. The most prominent uses of AI in higher education are attached to applications designed to protect or preserve academic integrity through the use of plagiarism-detection software (60%) and proctoring applications (42%) (see figure 1).
The chatbots are coming! A sizable percentage (36%) of respondents reported that chatbots and digital assistants are in use at least somewhat on their campuses, with another 17% reporting that their institutions are in the planning, piloting, and initial stages of use (see figure 2). The use of chatbots in higher education by admissions, student affairs, career services, and other student success and support units is not entirely new, but the pandemic has likely contributed to an increase in their use as they help students get efficient, relevant, and correct answers to their questions without long waits.Footnote10 Chatbots may also liberate staff from repeatedly responding to the same questions and reduce errors by deploying updates immediately and universally.
AI is being used for student success tools such as identifying students who are at-risk academically (22%) and sending early academic warnings (16%); another 14% reported that their institutions are in the stage of planning, piloting, and initial usage of AI for these tasks.
Nearly three-quarters of respondents said that ineffective data management and integration (72%) and insufficient technical expertise (71%) present at least a moderate challenge to AI implementation. Financial concerns (67%) and immature data governance (66%) also pose challenges. Insufficient leadership support (56%) is a foundational challenge that is related to each of the previous listed challenges in this group.
Current use of AI
Chatbots for informational and technical support, HR benefits questions, parking questions, service desk questions, and student tutoring
Research applications, conducting systematic reviews and meta-analyses, and data science research (my italics)
Library services (my italics)
Recruitment of prospective students
Providing individual instructional material pathways, assessment feedback, and adaptive learning software
Proctoring and plagiarism detection
Student engagement support and nudging, monitoring well-being, and predicting likelihood of disengaging the institution
tech cycle definition:
A tech cycle is usually a 30-35 year-long period that begins with the early commercialization of a group of technologies and ends with the mass adoption and daily use of the technologies by consumers, businesses and organizations.
Predictions For the XR Tech Space
Some predict the rise of AR glasses, leading to the death of smartphones. Others dream of a future where VR replaces the need to go to a physical office, with most meetings taking place in virtual environments. AI will come to life with AI-controlled avatars participating in VR worlds and advising as our own AR advisors and consultants.
We are still in the early innings of this tech cycle, we are looking at the beginning of the adoption of AR, VR, and AI (mass adoption is quite a few years out). This inevitable future has been accelerated by COVID-19, as many have turned to virtual reality and augmented reality as ways to socialize while keeping a social distance.
The specific AI — GPT-3, for Generative Pre-trained Transformer 3 — was released in June 2020 by OpenAI, a research business co-founded by Elon Musk. It was developed to create content with a human language structure better than any of its predecessors.
According to a 2019 paper by the Allen Institute of Artificial Intelligence, machines fundamentally lack commonsense reasoning — the ability to understand what they’re writing. That finding is based on a critical reevaluation of standard tests to determine commonsense reasoning in machines, such as the Winograd Schema Challenge.
Which makes the results of the EduRef experiment that much more striking. The writing prompts were given in a variety of subjects, including U.S. History, Research Methods (Covid-19 Vaccine Efficacy), Creative Writing, and Law. GPT-3 managed to score a “C” average across four subjects from professors, failing only one assignment.
Aside from potentially troubling implications for educators, what this points to is a dawning inflection point for natural language processing, heretofore a decidedly human characteristic.
he two highest-ranked spots went to skills that didn’t appear at all on WEF’s previous list: 1) analytical thinking and innovation, and 2) active learning and learning strategies. Another skill cluster that didn’t make the previous list debuted at No. 5 — resilience, stress tolerance, and flexibility.
“The pace of technology adoption is expected to remain unabated and may accelerate in some areas,” including the use of robots and artificial intelligence, the report said. Most businesses — 84 percent — plan to accelerate the digitalization of work processes and the use of digital tools, such as video conferencing,
People who behaved in accordance with them—for example, by staying away from the overgrown pond bank where someone said there was a viper—were more likely to survive than those who did not.
Compounding the problem is the proliferation of online information. Viewing and producing blogs, videos, tweets and other units of information called memes has become so cheap and easy that the information marketplace is inundated. My note: folksonomy in its worst.
At the University of Warwick in England and at Indiana University Bloomington’s Observatory on Social Media (OSoMe, pronounced “awesome”), our teams are using cognitive experiments, simulations, data mining and artificial intelligence to comprehend the cognitive vulnerabilities of social media users. developing analytical and machine-learning aids to fight social media manipulation.
As Nobel Prize–winning economist and psychologist Herbert A. Simon noted, “What information consumes is rather obvious: it consumes the attention of its recipients.”
attention economy
Our models revealed that even when we want to see and share high-quality information, our inability to view everything in our news feeds inevitably leads us to share things that are partly or completely untrue.
Frederic Bartlett
Cognitive biases greatly worsen the problem.
We now know that our minds do this all the time: they adjust our understanding of new information so that it fits in with what we already know. One consequence of this so-called confirmation bias is that people often seek out, recall and understand information that best confirms what they already believe.
This tendency is extremely difficult to correct.
Making matters worse, search engines and social media platforms provide personalized recommendations based on the vast amounts of data they have about users’ past preferences.
pollution by bots
Social Herding
social groups create a pressure toward conformity so powerful that it can overcome individual preferences, and by amplifying random early differences, it can cause segregated groups to diverge to extremes.
Social media follows a similar dynamic. We confuse popularity with quality and end up copying the behavior we observe.
information is transmitted via “complex contagion”: when we are repeatedly exposed to an idea, typically from many sources, we are more likely to adopt and reshare it.
In addition to showing us items that conform with our views, social media platforms such as Facebook, Twitter, YouTube and Instagram place popular content at the top of our screens and show us how many people have liked and shared something.Few of us realize that these cues do not provide independent assessments of quality.
programmers who design the algorithms for ranking memes on social media assume that the “wisdom of crowds” will quickly identify high-quality items; they use popularity as a proxy for quality. My note: again, ill-conceived folksonomy.
Echo Chambers
the political echo chambers on Twitter are so extreme that individual users’ political leanings can be predicted with high accuracy: you have the same opinions as the majority of your connections. This chambered structure efficiently spreads information within a community while insulating that community from other groups.
socially shared information not only bolsters our biases but also becomes more resilient to correction.
machine-learning algorithms to detect social bots. One of these, Botometer, is a public tool that extracts 1,200 features from a given Twitter account to characterize its profile, friends, social network structure, temporal activity patterns, language and other features. The program compares these characteristics with those of tens of thousands of previously identified bots to give the Twitter account a score for its likely use of automation.
Some manipulators play both sides of a divide through separate fake news sites and bots, driving political polarization or monetization by ads.
recently uncovered a network of inauthentic accounts on Twitter that were all coordinated by the same entity. Some pretended to be pro-Trump supporters of the Make America Great Again campaign, whereas others posed as Trump “resisters”; all asked for political donations.
a mobile app called Fakey that helps users learn how to spot misinformation. The game simulates a social media news feed, showing actual articles from low- and high-credibility sources. Users must decide what they can or should not share and what to fact-check. Analysis of data from Fakey confirms the prevalence of online social herding: users are more likely to share low-credibility articles when they believe that many other people have shared them.
Hoaxy, shows how any extant meme spreads through Twitter. In this visualization, nodes represent actual Twitter accounts, and links depict how retweets, quotes, mentions and replies propagate the meme from account to account.
Free communication is not free. By decreasing the cost of information, we have decreased its value and invited its adulteration.
Ren, a former engineer with the People’s Liberation Army who went into consumer electronics, played the patriotic card, cautioning Jiang that ‘switching equipment technology was related to national security, and that a nation that did not have its own switching equipment was like one that lacked its own military’ (1). A quarter of a century later, other countries, led by the US, have belatedly grasped the wisdom of Ren’s remarks; the technology in question today is 5G
The company operates networks in 170 countries and employs more than 194,000 people.
This summer it overtook Samsung as the world’s biggest seller of smartphones… boast some of the most advanced artificial intelligence capabilities on the market.
spending more than 10% of its annual profits on research and development. In 2019 it spent over $15bn — more than Apple and Microsoft — and the budget for 2020 is $20bn. (For comparison, the R&D spend of the entire German car industry in 2018 was roughly $30bn.)
Huawei and 5G are only a small part of a much larger geoeconomic and geopolitical struggle in which China is trying to gain the upper hand over the US.
Washington’s campaign against Chinese tech includes firms such as the state-owned ZTE, another important player in the 5G field, WeChat and TikTok and many other lesser-known companies. But Huawei is its main target.
Washington sees Huawei as an arch-example of China’s rogue behaviour (widely mistaken for meritocratic market success) — stealing intellectual property, bullying partners and undercutting competitors
Last year, Australia’s Chief Scientist Alan Finkel suggested that we in Australia should become “human custodians”. This would mean being leaders in technological development, ethics, and human rights.
A recent report from the Australian Council of Learned Academies (ACOLA) brought together experts from scientific and technical fields as well as the humanities, arts and social sciences to examine key issues arising from artificial intelligence.
A similar vision drives Stanford University’s Institute for Human-Centered Artificial Intelligence. The institute brings together researchers from the humanities, education, law, medicine, business and STEM to study and develop “human-centred” AI technologies.
Meanwhile, across the Atlantic, the Future of Humanity Institute at the University of Oxford similarly investigates “big-picture questions” to ensure “a long and flourishing future for humanity”.
The IT sector is also wrestling with the ethical issues raised by rapid technological advancement. Microsoft’s Brad Smith and Harry Shum wrote in their 2018 book The Future Computed that one of their “most important conclusions” was that the humanities and social sciences have a crucial role to play in confronting the challenges raised by AI
Without training in ethics, human rights and social justice, the people who develop the technologies that will shape our future could make poor decisions.
Information literacies (media literacy, Research Literacy, digital literacy, visual literacy, financial literacy, health literacy, cyber wellness, infographics, information behavior, trans-literacy, post-literacy)
Information Literacy and academic libraries
Information Literacy and adult education
Information Literacy and blended learning
Information Literacy and distance learning
Information Literacy and mobile devices
Information Literacy and Gamification
Information Literacy and public libraries
Information Literacy in Primary and Secondary Schools
Information Literacy and the Knowledge Economy
Information Literacy and Lifelong Learning
Information Literacy and the Information Society
Information Literacy and the Multimedia Society
Information Literacy and the Digital Society
Information Literacy in the modern world (e.g trends, emerging technologies and innovation, growth of digital resources, digital reference tools, reference services).
The future of Information Literacy
Workplace Information Literacy
Librarians as support to the lifelong learning process
Digital literacy, Digital Citizenship
Digital pedagogy and Information Literacy
Information Literacy Needs in the Electronic Resource Environment
Integrating Information Literacy into the curriculum
Putting Information Literacy theory into practice
Information Literacy training and instruction
Instructional design and performance for Information Literacy (e.g. teaching practice, session design, lesson plans)
Information Literacy and online learning (e.g. self-paced IL modules, online courses, Library Guides)
Information Literacy and Virtual Learning Environments
Supporting users need through library 2.0 and beyond
Digital empowerment and reference work
Information Literacy across the disciplines
Information Literacy and digital preservation
Innovative IL approaches
Student engagement with Information Literacy
Action Literacy
Information Literacy, Copyright and Intellectual Property
Information Literacy and Academic Writing
Media and Information Literacy – theoretical approaches (standards, assessment, collaboration, etc.)
The Digital Competence Framework 2.0
Information Literacy theory (models, standards, indicators, Moscow Declaration etc.)
Information Literacy and Artificial intelligence
Information Literacy and information behavior
Information Literacy and reference services: cyber reference services, virtual reference services, mobile reference services
Information Literacy cultural and contextual approaches
Information Literacy and Threshold concepts
Information Literacy evaluation and assessment
Information Literacy in different cultures and countries including national studies
Information Literacy project management
Measuring in Information Literacy instruction assessment
New aspects of education/strategic planning, policy, and advocacy for Information Literacy in a digital age
Information Literacy and the Digital Divide
Policy and Planning for Information Literacy
Branding, promotion and marketing for Information Literacy
Cross –sectorial; and interdisciplinary collaboration and partnerships for Information Literacy
Leadership and Governance for Information Literacy
Strategic planning for IL
Strategies in e-learning to promote self-directed and sustainable learning in the area of Information Literacy skills.
