As we rely more on natural language processing to help us navigate our world, it's more important than ever that these artificial intelligence models -- used increasingly in applications such as caption generation for the visually impaired -- remain true to reality. "The issue is that deep learning-based neural language generation models have no guarantees in generating factually correct sentences that are faithful to the input data," said UC Santa Barbara computer scientist William Wang. Over the many iterations it takes for a language generation model to learn how to describe or predict what a scene depicts, elements can creep in, causing phenomena such as errors in data-to-text translations or object hallucinations, in which the caption contains an object or an action that doesn't exist in the image. As a result, unless you have a way of reining in these errors (or you're surrealist painter René Magritte) these mismatches could spell the end of the usefulness of the language generation model being used. "This is a huge problem," said Wang. "Imagine you are using a news summarization system to read earnings reports -- the loss of faithfulness can give you wrong numbers, wrong facts and misinformation. Similarly, if a visually impaired person relies on an image captioning system to see the environment, wrong generation could create serious consequences."
High school senior Isabell Diaz has a routine. She rolls out of bed half an hour before her 9 a.m. On breaks, she steps away from the screen to eat breakfast or complete chores. She has learned how to navigate online assignments and virtual club meetings. So when she learned that her school would open in late April, she had mixed emotions.
Tabatha Plew quit her good-paying construction job in August, pulled her kids out of a Central Valley school they loved and moved seven hours north to this tiny town in Trinity County. Like a lot of rural communities, Weaverville in recent years has seen more people leaving than arriving, but it had a golden commodity Plew couldn't find at home in Fresno County for her three children: open classrooms that promised a desk in front of a teacher. "I packed them up, and I told my husband, 'We love you. See you on the weekends,'" said Plew, who moved into her in-laws' home in Weaverville. "This was the highest-paying job I've ever had, and, you know, the money didn't mean anything when my kids were struggling."
Artificial Intelligence innovation continues apace - with explosive growth in virtually all industries. So what did the last year bring, and what can we expect from AI in 2021? In this article, I list five trends that I saw developing in 2020 that I expect will be even more dominant in 2021. MLOps ("Machine Learning Operations", the practice of production Machine Learning) has been around for some time. During 2020, however, COVID-19 brought a new appreciation for the need to monitor and manage production Machine Learning instances.
As Women in AI Education Ambassador for Australia Angela Kim told Women's Agenda: AI tech is evolving at the "speed of light", while much about machine learning models can be automated, human must be included in its creation – which means the potential for human bias. Women's Agenda spoke to Charles Sturt University, Associate Professor in Computer Science, Lihong Zheng, who has lectured in mathematics and computer science since 2008. Lihong believes encouraging women to pursue careers in STEM begins in early primary school and continues throughout high school. Lihong started her career at a time when there were even fewer women working in STEM, particularly in Australia. Great mentors and having more women leaders in technology and science make it more accessible for girls to pursue degrees in STEM.
With health metrics improving and mitigation measures in place across Massachusetts schools, Elementary and Secondary Commissioner Jeff Riley said Tuesday it's time to begin the process of getting more students back into classrooms. Riley, who is set to join Gov. Charlie Baker and Education Secretary James Peyser for a 2 p.m. press conference on education and COVID-19, told Board of Elementary and Secondary Education members that he plans to ask them in March to give him the authority to determine when hybrid and remote school models no longer count for learning hours, as part of a broader plan to return more students to physical school buildings. Riley said he would take a "phased approach to returning students into the classrooms, working closely with state health officials and medical experts." He said his plan would focus on elementary school students first, with the initial goal of having them learning in-person five days a week this April. "At some point, as health metrics continue to improve, we will need to take the remote and hybrid learning models off the table and return to a traditional school format," Riley said.
Saving the Los Angeles school year has become a race against the clock -- as campuses are unlikely to reopen until teachers are vaccinated against COVID-19 and infection rates decline at least three-fold, officials said Monday. The urgency to salvage the semester in L.A. and throughout the state was underscored by new research showing the depth of student learning loss and by frustrated parents who organized statewide to pressure officials to bring back in-person instruction. A rapid series of developments Monday -- involving the governor, L.A. Unified School District, the teachers union and the county health department -- foreshadowed the uncertainties that will play out in the high-stakes weeks ahead for millions of California students. "We're never going to get back if teachers can't get vaccinated," said Assemblyman Patrick O'Donnell (D-Long Beach), who chairs the state's Assembly Education Committee and has two high schoolers learning from home. He expressed frustration that educators are not being prioritized by the L.A. County Health Department even as teachers in Long Beach are scheduled for vaccines this week. Although Long Beach is part of L.A. County, it operates its own independent health agency.
Contributions: The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education and evaluated its efficacy. While AI is conventionally taught in tertiary level education, our co-creation process successfully developed the curriculum that has been used in secondary school teaching in Hong Kong and received positive feedback. Background: AI4Future is a cross-sector project that engages five major partners - CUHK Faculty of Engineering and Faculty of Education, Hong Kong secondary schools, the government and the AI industry. A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum. This team formation bridges the gap between researchers in engineering and education, together with practitioners in education context. Research Questions: What are the main features of the curriculum content developed through the co-creation process? Would the curriculum significantly improve the students perceived competence in, as well as attitude and motivation towards AI? What are the teachers perceptions of the co-creation process that aims to accommodate and foster teacher autonomy? Methodology: This study adopted a mix of quantitative and qualitative methods and involved 335 student participants. Findings: 1) two main features of learning resources, 2) the students perceived greater competence, and developed more positive attitude to learn AI, and 3) the co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms.
In December, the University of Texas at Austin's computer science department announced that it would stop using a machine-learning system to evaluate applicants for its Ph.D. program due to concerns that encoded bias may exacerbate existing inequities in the program and in the field in general. This move toward more inclusive admissions practices is a rare (and welcome) exception to a worrying trend in education: Colleges, standardized test providers, consulting companies, and other educational service providers are increasingly adopting predatory, discriminatory, and outright exclusionary student data practices. Student data has long been used as a college recruiting and admissions tool. In 1972, College Board, the company that owns the PSAT, the SAT, and the AP Exams, created its Student Search Service and began licensing student names and data profiles to colleges (hence the college catalogs that fill the mail boxes of high school students who have taken the exams). Today, College Board licenses millions of student data profiles every year for 47 cents per examinee.
Among the things I have not missed since entering middle age is the sensation of being an absolute beginner. It has been decades since I've sat in a classroom in a gathering cloud of incomprehension (Algebra 2, tenth grade) or sincerely tried, lesson after lesson, to acquire a skill that was clearly not destined to play a large role in my life (modern dance, twelfth grade). Learning to ride a bicycle in my early thirties was an exception--a little mortifying when my husband had to run alongside the bike, as you would with a child--but ultimately rewarding. Less so was the time when a group of Japanese schoolchildren tried to teach me origami at a public event where I was the guest of honor--I'll never forget their sombre puzzlement as my clumsy fingers mutilated yet another paper crane. Like Tom Vanderbilt, a journalist and the author of "Beginners: The Joy and Transformative Power of Lifelong Learning" (Knopf), I learn new facts all the time but new skills seldom.