So let's continue, let's move forward with the program.
Now it's Sergio's turn.
I can't see him.
I couldn't see him because he was behind me.
So Sergio can either be there or here as you prefer.
He's the deputy vice rector for technological innovation
and he is going to introduce...
I think he's one of the most active members of our team.
He has a lot to talk about.
And I'm sure that his presentation will be really interesting for you.
I'm going to say thank you for the invitation,
the direction of the Central Library.
Also congratulations for this magnificent congress.
Well, my talk...
I'm sorry, I'm going to talk in Spanish because I wasn't sure
whether it was in English or in Spanish.
So I prepared it in Spanish and I'm going to talk in Spanish.
My talk is about artificial intelligence
and how it impacts in learning and in education institutions.
And this is something that affects all of us
in a very close way, mainly during the last two years.
Basically, what is happening is that we are living since...
Yeah, two years, I was saying, a Tsunami of
artificial generative, artificial intelligence tools.
CGPT has always been in the head of all the tools for many of us.
Previously, we already had many tools, mainly image generation by AI.
But it was when CGPT appeared that our scenario changed.
And each week we get, I would say, hundreds of new tools
that we can apply to every sector of our society.
And of course, among these sectors, the
education sector is one that is being affected.
So in this presentation, we're going to see how these tools...
how these tools are impacting in our education world.
I always compare this fact, two years ago, when this CGPT appeared,
I compare it to when Steve Jobs presented iPhone on 2017.
By this time, this type of phones already existed,
but this man created a completely new device with
new applications, and it made our society change.
From that day on, we started to communicate differently.
We didn't call as much, we sent more messages,
we made pictures different, we don't always carry a camera with us,
but we make the pictures with our phone,
we entertain ourselves differently, we communicate differently.
So from that moment on, in 2017, our society changed.
You just have to go to the suburban train
to check how everyone is always on their phones.
And I think that the same happened two years ago with Chad GPT.
That is going to change many different
aspects of our daily lives in society.
And it's getting through different tools,
well, Chad GPT and other tools, are going to change our society.
And this had already happened in the history.
Here we see an image of the first industrial revolution in Manchester,
where the workers were afraid, because this new vapor machine
that was created was taking their job away from them.
So they were panicking and they started
to destroy it to keep their jobs.
In many occasions, this is happening now,
and many people are feeling this with the
arrival of the artificial intelligence.
People thinking, "Ok, now these new tools are doing my job quickly.
" So many people may want to destroy this Chad GPT,
but this is not as easy as to destroy this machine in the picture.
But well, it is normal to feel these doubts, because it is true.
The society and the world, the work, is going to change.
Because not the artificial intelligence, but someone
that manages it, is going to take our job away.
Because they are going to do our job much faster.
So, there is going to be a change in the labor market,
and in every industrial revolution we are going to adapt to it,
and we are going to keep on moving forward.
And in the education sector this happened all the time.
For example, with calculators, math teachers,
they were complaining because they were saying
that the students would not be able to calculate themselves,
because up until that moment in the classes
they would teach to calculate with these huge numbers.
And from the position of the calculators,
well, they don't need to learn to calculate as much.
It is ok to be able to do these short calculations,
but they don't need to calculate as much.
So, they had to adapt their way of teaching, what they teach,
and they had to change how they evaluated,
and how they assessed what they were teaching.
This was a big change for them,
but nowadays the use of calculators is normal, it is common.
In many subjects it is forbidden to use the calculators,
but in many others calculators are just supporting the work.
So, now it is having the same.
And we are at a very important moment in the education institutions,
because we have to know the goals that we
have ahead of us, there are many of them,
because new technology is going to make us change many things.
But we also have to be conscious
and get to know the opportunities that it offers us,
that are a lot, and to get to know these opportunities
it is through training and education.
We have to understand that we can engage many processes
and do things that two years ago we could not even think about them,
and today we can and we are able to do
them in different processes and speeds.
Before I was talking about the first Tsunami of AI tools,
but I think that we also have a second Tsunami,
that this time is about tests of continuous evaluation generated by AI.
So, mainly the teachers say that they
are getting many homework done by AI
and it is really difficult to distinguish it from a real task.
This is difficult and we have to take this into account,
because we are going to have to change the way we teach.
So, I wanted to show you here some examples
of how this new technology is impacting
our continuous and comprehensive evaluation tests.
Here I bring an example from a test of a subject
and I say to JATTP, tell me the right answer for these questions.
And in some seconds JATTP gives me the answer,
the right answer probably, not all of them are going to be right,
but most of them are going to be correct.
So, imagine I have a subject and I set an online test,
it is very easy that my students can answer it with this tool.
Same way.
Ok, so this is a program that with this technology did official exams,
like for example the exams the lawyers
have to do once they finish their degree.
So, they finish their degree and they
have to do a test to obtain their license.
And it turns out that this technology, it is the 90 profile,
this means that for each 100 lawyers the
technology answers better than 90 of them.
This means that this new technology is able to
answer to the questionnaires in a better way.
So, maybe we have to rethink about this test
and questionnaires to decide when to use them.
The same way for ESA or development tasks.
Here, this is an example, I write here
something about one subject of mine
and then JATTP starts to give me an answer about it.
Here I ask him about the differences
about the different types of computation
and then JATTP starts to describe the different types of computation.
Well, I would say that this answer is a little
bit poor, that wouldn't pass my subject.
This is a chat, I could say, ok, I don't like
it like this, maybe do it this other way,
focus more on the differences and maybe at
the third try it would give a right answer.
So, here I said specify better the difference
between the different types of computation
and this second answer is already a little bit better and
maybe this second or third answer will pass my subject.
So, we know that there is also this risk, this
risk exists if this is our type of assessment.
In my type of subject that my students
have to program different softwares,
these tools can also program even better
than me and they also comment on it.
So, imagine I say something about a task in my subject and
in some seconds anyone can get the answer through JATTP.
So, yeah, as I was saying, maybe not the first answer
but the second or third would be the perfect answer.
So, in my trainings I ask for my students to do a data analysis.
Well, the tools can also do this data
analysis and do graphics and schemes.
So, well, this is not a solution as well.
So, what can we do with the integration?
I see four options.
The first option is ignore it and say, ok, this is
something that is not going to exist in a couple of years,
it won't exist anymore, but the truth is that this
is here to stay and this is just going to get better.
Today there are some mistakes, some fake answers that
the AI gives, but this is just going to get better.
The second option is to forbid it.
In our institution 5, we could avoid that the students could use this AI,
so the students couldn't access these tools through our campus,
but they could access it through their
own computers, their personal computers.
So, yeah, this wouldn't work as well.
We could hope that they would do it and they would
lie to us, but that's something we cannot control.
The third thing we could do is use the
ancient tools of AI-generated text,
but the truth is that these tools do not work
perfectly, so we cannot trust them and we cannot hope.
Well, we cannot depend on this option.
So, the only thing I think we can do
is to evaluate our way of assessment.
In real life, if the students go to the real
life, they are going to use these tools,
so this means they are going to have a
new workmate, that in this case is AI,
so it might make sense that they are able
to use it and that we take it into account.
And maybe we don't ask the students for the
same things we used to ask two years ago,
because when they go out to the real life they will work differently,
because they will always have these tools as a workmate.
So, here I have some recommendations
based on my experience on how can we adopt
these continuous and comprehensive evaluation tests.
The first is, if our subject is questionnaires like these ones,
maybe these questionnaires would be
better to leave them to self-assessment,
because it is very probable that they can solve it with AI.
But, well, we can use them as a training for self-assessment.
Or we can do tests in paper, they have to fill it with a pen.
But if we want it online, maybe it wouldn't work,
this type of evaluation, this type of tests.
Maybe where it makes sense is to ask the
students to integrate the use of these tools
in the evaluation tests, that part
of the training is to use these tools
in order to research about something and
then do an additional work based on that.
That is what they are going to do in real life, in the real market.
Another thing we can do is to do personal evaluations, so in class.
In UNED we are a distant university, so it is difficult.
Well, for other institutions or educational centers maybe it is easier,
because face to face there is not the risk of using chat-dpt.
You ask a student a question and you know if they can answer it or not,
or if they are using these tools on their daily life basis or not.
Another thing that I do is I ask students
to use tools that are not easy to
use, that chat-dpt cannot use as easy.
And what we have to do is not just to evaluate the final result,
but to assess how the student progressed.
This is more work for us, but we have to
evaluate that they don't go from 0 to 10
in one minute, because that is a little bit suspicious.
And something that we also have to ask the students for is.
that they have to talk about the AI that they have used.
If our students have used AI in some way in their tasks or homework,
they should write about it.
And me as a teacher, I think it is
interesting what they ask the AI to do,
and what was the answer of the chat-dpt, for example.
And so I can evaluate what does the student know.
This for me is very interesting.
So I think we have to work towards
transparency in the use of AI in the tasks,
because we cannot avoid it, it is going to be the daily reality.
Also, here I have an example of APA, how to reference AI.
If our students have used it, what it
proposes is that in the author field
we can put the tool, if it is chat-dpt we can write down OpenAI,
that is the company, the year, the name, the chat-dpt,
in this case the version number, the model type,
the large language model, and the URL of the tool.
So this is how APA suggests that we can refer to the use of AI.
And I think it would be interesting
to include a new section in the tasks
that is a reflection about the use of tools.
And in this the student must clarify what did they ask to the AI,
what were the answers, which answers
were right, which answers were wrong,
where did the student have to look for additional references,
many aspects that for me as a teacher it is interesting to evaluate
what the student learned.
We as teachers have also worked, we have to indicate clearly
what do we want the students to do, how
do we want the students to use the AI.
For me, for example, I don't mind that the AI creates hypotheses
or does translations or corrects a text,
but maybe I don't want them to use it to create the answer.
So we have to identify what can they use the AI for or not.
In their continuous and comprehensive evaluation test
as well as in their final master and degree tasks.
So we talked about some of the risks at an academic level
that exist with the use of these tools.
As we were saying at the beginning, there are also some opportunities
that are in front of us and each day we
have new tools that can be useful for us.
So, some of the functionalities that are useful
for students and for teachers are these ones.
For example, when we think about new tasks,
the white paper does not exist anymore.
We have a first idea, a first draft for which we can work.
For example, last summer I wrote an adventure book
with my daughter, 8 years old, and I wrote on ChatGPT
"Give me some ideas to write an adventure book for an 8-year-old girl".
And ChatGPT gave me some ideas and then with
these ideas I said "Ok, now give me a title".
And then "Ok, now give me how the chapters look like".
And then I would ask "Give me an instructor
for the first and second chapters".
And so in some minutes we wrote a whole book
and then my daughter read it and said "Ok, wow, I liked it
as well as I liked the ones from the store".
So we have to understand that we can use
it to accelerate many creative processes.
We can also use it to ask for clear explanations.
For example, for complex concepts we
can use this technology to clarify them.
We can use them to translate text and to enhance the style.
And students can use it as well from many
points of view that might not be a fraud.
They can use it to reinforce the concepts
or maybe before sending me the task to identify mistakes
with these tools before sending them
to me so they can have a first feedback
and enhance their task before sending it to me.
I'm a little bit afraid that the students use these kind of tools
because the tool can give a wrong answer.
And if they don't have enough knowledge
they might believe in this mistake and learn it wrongly.
I always say I wouldn't use a certificate or any of these tools
to learn to make my own diet, for example,
because I don't know anything about nutrition
and everything they say I read a bit
and maybe I would do something wrong for my own health.
I just use it for things that I know.
So if I have to program something, for example,
I use these tools because it's faster
and I know about the topic already so they cannot trick me.
But in other topics I don't know about,
for example, nutrition, I wouldn't use it.
So I always recommend to use these tools
when you don't have the knowledge about the
topic you are asking about, the LGBT or the AI.
And the students may not have enough knowledge
to know when the tools are making a mistake.
And for teachers they can be so useful as well for many things,
for brainstorming, for question drafts, to sum up or amplify texts,
to generate didactic content, to generate rubrics,
schemes, to create images, videos, avatars.
We are going to see some examples of this now.
We can do diagrams, we can generate images,
as I was saying.
Here you say, "Okay, give me images of a man sitting in a desk
with a skyscraper in the background.
" And within some seconds you have an image
of what you were thinking about, an image created for you.
For example, I myself, in some occasions,
I generate videos with my own virtual avatars.
Here is an example.
Okay, well, this is a video I did not record.
I just generated the text by my avatar.
I wanted my avatar to say,
well, then my avatar just said the text I created.
And I could do this in Spanish, in Chinese,
or in Spanish, in Spanish, in English,
in Spanish, in English, in Spanish, in Spanish, in
English, in Spanish, in Spanish, in English, in Spanish,
in Chinese, or in whatever language I want.
So this opens a brand of new opportunities
also when trying to personalize information.
It also generates, well, there is this new tendency
of new tools appearing, that allow us to generate any kind of videos.
You can say, "Okay, I want a video about a woman walking in Tokyo
after rain, and it generates this kind of video.
So, our visual generation is changing, and probably in one year or two,
it's going to be two different Hollywood movies
that are going to be created in a very different way
as they used to be, as close as two years ago.
But also in education, there are many
tools and many functionalities we can use.
For example, this tool, Jenny,
shows us, for example, if I write a sentence,
this tool looks for citations that are,
that do agree with what I just said.
And this helps me to look for these
references to the text that I'm writing.
Or, for example, Elicit is another tool.
I write here the research question that I want.
How effective is this product, for example?
And they create this table,
and this comes from a real scientific repository.
It's not made up. It is real.
And they generate this scheme to sum up everything.
And it is funny because these columns are dynamic.
I can change, I can select the name,
and they're going to look in all the articles and redo the scheme.
If I had to do this by hand, like reading
all the articles, it would take hours.
But with the tool, with some minutes, I can have it done.
There are other different tools, like SciSpace.
It's the same.
You put a research question.
How does climate change impact biodiversity, for example?
And they create this scheme,
they sum up the scheme with the real references.
And the difference of this tool is that it has a chat.
So that you can talk to it
as if you were talking to the authors of this essay.
You ask to the chat,
and they answer you as if you were talking to the author.
These are things that two years ago were not even possible.
For example, Confluences is another
interesting tool on which it's the same.
We set a question, "Does creatine help to build muscle?
" It generates this as well,
but it has this tool that is called consensus-building
that tells you the percentage of people
that agree or disagree with this hypothesis.
So you can validate it in seconds.
Also in the UNED, we have developed some tools based on AI.
So that students, doctorate students,
know where to publish their articles.
So they write down the title and the sum up of their article.
And it gives them some indication
about in which journals they can publish or not.
So, for example, based on your specific sum
up of your essay, these specific journals
do agree with your essay.
So you could publish here, this is Q1, this is Q2.
So we can use this tool that didn't exist some years ago.
And something we have to take into
account, apart from all we've talked about,
all the opportunities and difficulties, is that it has its limitations.
There are some limits in the use of these tools.
The first one is that these technologies make mistakes.
It's what in the AI we say to hallucinate, these tools hallucinate,
they make mistakes, they make up preferences, dates, names.
It looks like it's real, but many times it is not.
So you don't have the knowledge, you just believe it.
And it's not right.
The second limit is that the answer is not always correct.
We always have to take this into account.
It looks like the answer is convincing, but it may be wrong.
If I ask, for example, how much is it 3 times 4 plus 9 times 9?
It gives me first the answer and then the explanation.
It gives me the answer and says the answer is 87.
Why? Because first we do these operations here,
and then we sum the results, and then we have the answer, 93.
You can see here that
the tool is saying two different answers.
First it says 87 and then it says 93.
So we have to know that these tools can make mistakes.
Because it's how they work.
Another thing that happens is that each time
we ask something, the answer might change.
If I ask, tell me how many names,
how many countries, names of the
countries, it starts with this letter V.
First time they say Venezuela, Vietnam, Ghana, too.
And the second time they include the Vatican.
Why? Because each time they follow a
different flow to create their answer.
So the answer might be different.
What other limits do they have?
Well, it has bias.
It has these limitations.
Why? Because these technologies are trained
on texts that are mainly occidental, that are close to North America.
So all the results that they're going to give
are going to be as limited as the existing texts in our country.
So, for example, we say translate to Spanish this text.
The nurse was so kind,
and they would translate it as "La enfermera fue muy amable.
" In Spanish, "la enfermera" in feminine is a woman.
But if you say "the pilot was so kind,"
it's translated in masculine, "El piloto
fue muy amable," that is like a man.
So it says that the nurse is a girl and the pilot is a guy.
And this is because this tool was trained with the text on which
all the pilots were men and nurses were women.
So this is something they do wrong.
And not only gender limits, but also race, age, and everything.
Also, the quality of the answer depends on
how good we make the instructions, depending on what we ask,
we're going to get a better or worse answer.
So in some way, somehow,
we have to learn how to interact with the machine, with the tool.
We have to understand how the tool can give us the best results.
And also there are privacy limits, privacy problems.
We must not share any personal data when we ask anything to the tool,
because they can be used, maybe for training.
We must not share confidential information
or information about the company, third-party
data, or protected content with copyright.
Imagine, I upload a book for the tool to analyze something.
Well, the tool is going to keep this book,
this submission of the book.
So we have to be careful about all these legal issues.
Just to end up, just to say that in DIONET
we have a section on which we're working about all this AI.
And we've generated a guide
so that the teachers and students understand the risks
and the opportunities that are behind these kind of technologies.
We've created a course,
an open course of AI for students.
And also we have another MOOC in the open courses platform of DIONET
that is called "Import and application
of generative artificial intelligence within
education", on which we're going to talk about
all these matters for students and for teachers.
And this is all.
I think I did it on time.
Thank you very much for your attention.
Do you have any questions or any comments?
Thank you.
So, when we talk about this matter,
I always think that we have the need to keep calm.
Because we think about the possible derivations
of all this that we're seeing, and what
you've talked about, and many other things.
And we have to keep calm.
Either we keep calm, or, well, I would say there's a fifth option.
Because you said ignore it, to forbid
it, or to change the evaluation system.
I would say there's another possibility,
that is to say, "OK, let's just lie down, not do anything,
because AI is not going to do anything.
" Well, not as if nothing happened,
because we would have to change everything in order to automate the AI.
Well, for me,
well, this is inevitable, this is obvious,
this is going to happen, this is happening.
So, we have to learn to deal with it in the best way possible.
But I think there's a powerful force in this human being,
that we always have to take into account
when we analyse these kind of tools.
But I think that it is not about like completing us, or helping us.
But now I think they are substituting us, they can substitute us.
And it's a huge, powerful human force that is lazy.
The human being is lazy.
So, in all this analysis, I always meet that dimension,
that aspect of what is a human being,
and taking into account how a human being is,
how are we going to be able, somehow, to give a sense to life,
having been able to use all these tools, tools that are going to prove
to our future that they are smarter than us, they are quicker than us,
all their answers are better than ours.
So, what's my role in life?
This is the question.
I know this has no answer.
Yeah, but if you realise what you're saying,
this is the feeling that this man trying to break the machine
I showed you in the Industrial Revolution had.
It's the same feeling.
We are now living the fourth Industrial Revolution.
And in each one of them, we always have the same feeling,
but then we adapt, and we create new jobs,
and so we all keep on working, and we all keep on moving forward.
But we always are afraid, we always have doubts, and we always think,
I'm going to be substituted, but well, not completely.
Mainly, they will help us,
they will do the tasks in a more efficient way,
but for sure we will always have work to do.
And what has happened, and it's the same as has happened
in the previous Industrial Revolutions.
Well, I don't know a lot about AI,
but I would like to know if there are studies
about reproduction, about what people ask to do,
well, you said that the question gives you an answer,
but then you can make more questions to get a better answer.
But if you will do the same trial tomorrow,
or for example, all of us today, now, if we did the same, what happens?
Well, we can get a different answer every time.
And if you ask this in two years, the system is going to be better,
and it is going to give you a better answer.
That's it.
And if you add details to the prompt, it will be more...
But that is a system that is not...
Well, it's a system that is not like Google, for example.
It is not just a searcher that gives you
the results, but each time it might follow
different information flow to prepare the answer,
so each time the answer might be different, it might be similar,
because they are going to try to be correct
and answer the same question, but they might differ.
I'm thinking now about that, for example,
these two answers are changing, they are always different,
but let's imagine that there is one correct answer.
So, would it answer to any kind of flow?
I mean, we have a balance, and the correct answer is in the middle.
I don't know completely about this, but if you
ask to the tool what is the capital of France,
it is going to tell you most of the time that it is Paris,
but not always, maybe some of the times it won't say the right answer.
It will depend on the type of question and how the question is made.
But we have to take into account this use mainly for our students,
because they do not believe in the answer
if they don't have the knowledge to evaluate
this answer, if it is correct or not.
I wanted to ask if we already have some teachers
that are comprehensive and friendly, that organize short sessions
and transversal sessions for their doctorate
students to explain them about Open Science
and open access and publications.
This is what PhD students are going to have to do in the future,
but they don't know about it because no one explains it.
So, I was asking myself if there is any option to include,
maybe we can talk about it in the round table,
but any option to include some basic guides
for them to apply the knowledge when they need to publish.
Because right now the students,
they are thinking a lot to try to identify texts made by Chathupy.
Would you think this would be easy to implant?
Yes, I actually think it is the only way.
But these are things that we are building all together.
These are goals that we are finding
and that we have to achieve all together.
The core that we have now opened,
it is a collaborative rule on which we do not give all the answers
to all the questions, but we just say that we all as a community
we are going to build the answers to all the goals.
Because, for example, I might have some answers in my field,
but in philosophy or writing I don't have the answers.
So, they will have to achieve their own goals.
So, all of us as a community will have to
work together and generate this knowledge.
Maybe a task would be for them to read
this book you talked about. How long is it?
Well, I think it is like 20 hours talking about the job and so on.
And everyone can do it at their own rhythm and they are open access.
So, they can access it.
There is another colleague here, Alexis,
I don't know if he wants to say something
about the contents that the library gives
in the doctorate programs about this.
Hello everyone. Sorry, my voice is a little bit short.
About the training given to the doctorates by us in the UNED this year,
we linked all the resources that they gave
from the education rectorate
and the guides there for teachers and students.
This year we are going to program a session
to present the tools that support the creation of research,
the ideas that they can give to it, make the tasks quicker and so on.
So, the idea is to combine the resources
existing and made by the rectorate with some sessions on which
they can check how these applications
work and maybe they can ask the doubts
they can have in this research process
because all these tools, Chantipiti and so on,
they have many applications, we can use them
from searching a biography.
It may not be the worst way of looking for a biography
because some citations can be invented,
but for other things, Chantipiti can, for example,
make better the English writing of some students
and it also has some advantages for the researcher
for example, to send a script to a journal
you can ask him the contents of the journal.
It saves you work in general,
but obviously you have to have a basic
knowledge of what you are asking and what for.
This idea we have to transmit to the doctorate students
that they must use it correctly and they must know
how to use it and they must know that the text
created by the tools, they cannot use it
without checking them because you don't know where they come from.
So, if you do that, you may be copying a text
from another paper and not talk about it
and here you will find an ethic problem.
So, in order to make your own work better
we should give this idea to the doctorate students
that these so useful tools, they have to use it with some knowledge
and knowing, as you were saying,
more about what they are asking than their own tool
because if you know what you are asking
then you will know if the answer is correct or not.
Any other question?
No? Ok.
So, thank you very much. Thank you everyone.