En aquesta entrada hi faig un resum d’alguns articles més que he anat trobat, i que complementen els dos anteriors de la sèrie
Exploring the impact of artificial intelligence on teaching and learning in higher education 
The current use of technological solutions such as ‘learning management systems’ or IT solutions to detect plagiarism already raise the question of who sets the agenda for teaching and learning: corporate ventures or institutions of higher education? The rise of techlords and the quasi-monopoly of few tech giants also come with questions regarding the importance of privacy and the possibility of a dystopian future. These issues deserve a special attention as universities should include this set of risks when thinking about a sustainable future.
recent advancements in non-invasive brain-computer interfaces and artificial intelligence are opening new possibilities to rethink the role of the teacher, or make steps towards the replacement of teachers with teacher-robots, virtual “teacherbots”
An example is offered by the course offered by Professor Ashok Goel on knowledge-based artificial intelligence (KBAI) in the online Master in Computer Sciences program, at Georgia Tech in the USA. The teaching assistant was so valued by students that one wanted to nominate her to the outstanding TA award. This TA managed to meet the highest expectations of students. The surprise at the end of the course was to find out that Jill Watson was not a real person, but a teacherbot, a virtual teaching assistant was based on the IBM’s Watson platform
We must be careful when we see the temptation to equate education with solutions provided by algorithms.
Teacherbots are already presenting as a disruptive alternative to traditional teaching staff, but it is very important to inquire at this point how do we use them for the benefit of students in the context of a profound rethink of what is currently labeled as ‘graduate attributes
Can artificial intelligence transform the teaching and learning experience? 
Many of us are using technology to do the same things that we’ve always done, but just on a technological platform,” she said. “We haven’t yet figured out what we can do that’s different as a result of the technology.”
It was agreed there was a need to give teaching staff more time and space to develop and implement change. It was also said that co-design with students and staff was crucial when developing tools to assist the education experience and that conversations should be data-informed rather than data-driven.
Explainable AI: The Rising Role Of Knowledge Scientists 
There is no trust without explainability. Explainability means that there are other trustworthy agents in the system who can understand and explain decisions made by the AI agent. Eventually, this will be regulated by authorities, but for the time being, there is no other option than making decisions made by AI more transparent. Unfortunately, it’s in the nature of some of the most popular machine learning algorithms that the basis of their calculated rules cannot be explained; they are just “a matter of fact.”
The machines are learning, and so are the students 
It is well established that the best education is delivered one-to-one by an experienced educator. But that is expensive and labor intensive, and cannot be applied at the scale required to educate large populations. AI helps solve that.
She uses Bakpax, which can read students’ handwriting and auto-grade schoolwork, and she assigns lectures for students to watch online while they are at home
“Education is going to be the killer app for deep learning,”
The world will still need schools, classrooms and teachers to motivate students and to teach social skills, teamwork and soft subjects like art, music and sports. The challenge for AI-aided learning, some people say, is not the technology, but bureaucratic barriers that protect the status quo.
In higher ed, not all chatbots are created equal 
It’s easy to think that AI can be the solution to all your problems. And all too often, chatbot developers tout the transformative impact of their products on student outcomes. But our experience with ACE has taught us that the technology itself is only part of the equation. How you implement it is just as important.
China has started a grand experiment in AI education. It could reshape how the world learns. 
A student begins a course of study with a short diagnostic test to assess how well she understands key concepts. If she correctly answers an early question, the system will assume she knows related concepts and skip ahead. Within 10 questions, the system has a rough sketch of what she needs to work on, and uses it to build a curriculum. As she studies, the system updates its model of her understanding and adjusts the curriculum accordingly. As more students use the system, it spots previously unrealized connections between concepts. The machine-learning algorithms then update the relationships in the knowledge graph to take these new connections into account. While ALEKS does some of this as well, Squirrel claims that its machine-learning optimizations are more limited, making it, in theory, less effective.
Dede says the kind of data generated in an intelligent classroom could be useful, but he cautions that cameras and other sensors could also be misused to judge a student’s emotions or state of mind, applications that have little grounding in science and could lead to over-surveillance. Pan agrees that it’s important to be careful: “That’s why we provide the data mainly for teachers and not students, because we haven’t yet run scientific tests.”
Demystifying AI: What’s Fiction, and What’s Worth Fanfare? 
– Myth #1: AI will replace jobs and maybe even humans.
– Myth #2: AI will ruin privacy.
Why are so many educational AI “solutions” total crap? Here’s a clue: Fewer than 9% of research papers on the use of AI in education have a first author with a background in education research. Ignoring years of education research is simply stupid 
I finalment…Why Solving a Rubik’s Cube Does Not Signal Robot Supremacy 
People see a human doing something, and they know how they can generalize. They see a robot doing something, and they over-generalize
Is Artificial Intelligence the Ultimate University Stimulus? 
If there’s one thing that makes studying at university better, it has everything you need to learn, study, and research wherever the student may be. Whether studying, learning or research takes place on the go or from home can be the students’ choice. Through a combination of online and offline education, artificial intelligence allows students to study where and when they want.
Twinning is effectively a solid starting point for the development of a proactive educational study plan. From here, as the data reflects the student’s actual profile, the near to real-time data of the students’ progress will represent the students’ knowledge and skills.
Claves para aprovechar la Inteligencia Artificial en la educación 
El tutor intel·ligent ajudarà a reduir la xifra de suspensos i abandonaments  (David Bañeres)
El futur no el decidiran les màquines. El decidirem les persones però amb un ús cada cop més intensiu de la intel·ligència artificial, que no és altra cosa que una extensió de la intel·ligència humana. Que la tecnologia augmenti la humanitat i no al revés.  (Xavier Marcet)