TELESUR — broadcast
20261104 110000 UTC
470 transcript segments
Google Cloud Speech-to-Text API (Chirp) + Gemini 2.5 Flash Non-Thinking
Data courtesy of The GDELT Project (https://www.gdeltproject.org/), from the Internet Archive TV News Archive.
Machine transcription. Treat it as a searchable index of what was broadcast, not a verbatim quotation record.

[00:00:00] mentioned the reopening of this route to the fulfillment of several
[00:00:03] demands, among them the lifting of sanctions, the
[00:00:07] release of blocked
[00:00:09] many people would stop at the assets and the recognition of its sovereignty over the
[00:00:12] strait.
[00:00:19] With this we close this broadcast of Telesur
[00:00:22] medicine, in science, in Noticias, thank you for your viewership, stay tuned to the Telesur screen, until
[00:00:26] next time.
[00:00:54] hallucination, not everything it
[00:01:07] advances that today have come out of
[00:01:21] Hello, welcome to text and context, it's great that you
[00:01:26] why do they do that, how do they follow us through our Telesur it doesn't come directly from Multimedia, today with another very
[00:01:28] interesting topic. Never before had we interacted with so many
[00:01:32] books, discovering books, talking about books, recommending them and
[00:01:39] used, uh, through we see many applications in even analyzing them on digital platforms. However, there is an accelerating trend that worries experts:
[00:01:42] artificial intelligence is
[00:01:44] changing the act of reading under automatic
[00:01:48] schemes and compressed
[00:01:50] it turns out that the researchers who are working on versions of books that replace the reflective and immersive process of
[00:01:54] traditional reading, with new applications that promise to finish, for
[00:01:57] example, a book in less than 10 minutes. Prioritizing speed over the
[00:02:01] depth of a work, is precisely what we are going to talk about today in text
[00:02:05] and context, with AI are we reading more, are we
[00:02:14] AI, book consumption increased. There are
[00:02:17] loyal readers of paper books, those who read digital
[00:02:21] already, everything we are reading in books, and those who prefer audiobooks, because
[00:02:23] reading is no longer an absolute experience and each
[00:02:27] reader can choose the way in which they approach a work,
[00:02:31] but this is far from those who ask AI for a summary of a
[00:02:34] book and with it assume they have read the work. This
[00:02:38] practice influences reading counters that measure
[00:02:43] reading are not developed. how much a work is consulted or read. AI
[00:02:46] has accelerated processes by making promises of applications to
[00:02:50] read a book in 10 minutes. These tools lead us to
[00:02:54] ask ourselves a necessary question. With the arrival of
[00:02:57] AI, does it mean that we are reading more? Well,
[00:03:01] there we had the profile of our program, I immediately move on to talk with my guests
[00:03:04] about the topic, in the studio I am accompanied by María
[00:03:08] Herrero, professor of the artificial intelligence career at the
[00:03:11] classical literature, in cases of what Humberto Fernández Morán University, thank you very much for your time with us and the
[00:03:16] stay with the information offered by the Latin American audience, also Lino Menéces from the General Directorate
[00:03:18] of Artificial Intelligence of the Ministry of Science and Technology,
[00:03:22] Lino, thank you also for your time with us, and from a distance I am also
[00:03:25] accompanied by Pablo,
[00:03:27] can be the product only of writer and philosopher, also an expert on this topic,
[00:03:30] thank you very much, Professor Pablo, for your time, to talk precisely
[00:03:34] about what we have commented on in
[00:03:37] the
[00:03:39] in some way and since they don't have what question that precisely
[00:03:42] makes this analysis possible, artificial intelligence and how it
[00:03:45] is precisely changing reading and writing
[00:03:48] habits, not only in
[00:03:51] education but also in
[00:03:53] train and well, one of any type of sector
[00:03:56] or factor that gives us reading, that
[00:04:01] our country. We have to start makes us read precisely text or an essay, whatever it is, artificial
[00:04:03] intelligence has been precisely one of the great
[00:04:07] challenges in terms of education, in terms of
[00:04:10] politics, of course, but also in literature and the way we are also
[00:04:14] approaching scientific essays.
[00:04:18] What to say about this? I'll start with you, María
[00:04:21] Paula, in this sense,
[00:04:23] because what some experts suggest is that the way artificial intelligence
[00:04:27] and social networks treat
[00:04:30] precisely the way
[00:04:34] start by differentiating of reading and writing is changing
[00:04:37] habits and the way we previously did it. What changes are you
[00:04:40] seeing? Are people reading more with artificial
[00:04:42] intelligence?
[00:04:46] Well, I wouldn't know if people are
[00:04:49] reading more with artificial intelligence, what I could tell you is
[00:04:53] that students or people are using
[00:04:56] it much more to try to research things and
[00:05:00] summarize, right? So we could say that instead of reading
[00:05:04] that's why they fall into hallucinations and a paper or reading a book or reading something for a
[00:05:09] gives you the critical task of seeing if what research, they first go to artificial intelligence to look for a summary. So that artificial
[00:05:13] intelligence summarizes it for them and based on that, they would then
[00:05:16] go on to read what follows, right? I suppose
[00:05:22] summary if they don't find it interesting, right, and they wouldn't read
[00:05:25] the complete work once they study
[00:05:29] the summary, however, there is concern because the way algorithms
[00:05:33] are treating the topics could
[00:05:36] even in artificial intelligence modify
[00:05:40] the content, there is also a concern, of course, because many
[00:05:44] people are currently using artificial intelligence as if it were a search engine or an
[00:05:47] exact summarizer of content and it is not
[00:05:51] like that, artificial intelligence is trained with a lot of
[00:05:53] information and when it gives you answers it is
[00:05:57] generating the answer word by word according to statistics and
[00:06:00] the frequency of words and an
[00:06:03] effect occurs that is called
[00:06:07] says is a hallucination but it can be hallucinating and can be
[00:06:11] inventing authors, these summaries
[00:06:13] essays, papers, therefore one cannot rely on what artificial
[00:06:17] intelligence tells you, you have to validate everything, right? It even
[00:06:21] evolved a bit and today it gives you the sources so that you can access
[00:06:24] the sources and validate, but even giving you the sources it sometimes
[00:06:28] hallucinates and invents sources, so there is always
[00:06:32] human work to validate that everything it is telling you
[00:06:36] is correct and not to assume it as correct, of course, Professor
[00:06:39] Pablo, are we reading more with artificial intelligence? Let's go to the topic of
[00:06:43] literature, because obviously on social
[00:06:46] networks, through the internet
[00:06:50] which they promise a person
[00:06:53] to read a book in 10 minutes and this is indeed
[00:06:57] changing the way we understand what reading is. Are we reading more,
[00:07:01] are we reading less with artificial
[00:07:02] intelligence?
[00:07:05] Well, first of all, I believe that
[00:07:09] artificial intelligence, like all scientific-technological revolutions that have
[00:07:12] occurred in the history of humanity, have challenging
[00:07:15] sides with positive and
[00:07:18] negative factors, they have dangers, right? It happened with the industrial
[00:07:22] revolution, with atomic energy, with the internet, in short, and the
[00:07:25] same can happen or is already happening with artificial
[00:07:29] intelligence. I believe that it is not bad or good in the archaeological
[00:07:32] sense, but depends on how it is used.
[00:07:36] I have the impression that students' reading
[00:07:39] at this moment, to a certain extent,
[00:07:43] is being partially affected in some
[00:07:47] cases when it is summarized, only those summaries
[00:07:51] are used and critical thinking, deep
[00:07:55] There is what artificial intelligence experts call a cognitive
[00:07:58] download because it is practically
[00:08:01] too easy. I agree with the professor in what she said
[00:08:05] that one first looks for a summary, that was done previously with
[00:08:09] before artificial intelligence appeared, the summaries
[00:08:12] or abstracts and then one would look for, let's say, if the article
[00:08:16] was of interest, but today what is happening
[00:08:19] is something that students and not
[00:08:23] only students, some researchers also,
[00:08:28] artificial intelligence summary that is not always really
[00:08:32] corresponds to reality or that does not
[00:08:35] take into account valuations that
[00:08:40] imaginative capacity. Let's not
[00:08:42] forget that Albert Einstein said
[00:08:45] that science advances more with
[00:08:48] imagination than with
[00:08:51] information and that imagination, Einstein said,
[00:08:54] develops more in art and literature
[00:08:57] than in mathematics. Yes, without a doubt
[00:09:00] it's a very interesting topic, especially
[00:09:03] distinguishing information from reading a book
[00:09:07] from the art of reading, Lino, because
[00:09:09] we obviously see with these networks,
[00:09:13] with all these
[00:09:16] and algorithms that well, they tell you, you can
[00:09:20] read a book in 10 minutes, however
[00:09:23] this is also used as a reading counter, this book is being read a lot,
[00:09:27] this book is not being read a lot, there is also an indicator on
[00:09:31] the internet that suggests that through
[00:09:34] this type, this format, more is being read, how do you
[00:09:38] see it as an artificial intelligence expert? Well, in the
[00:09:41] case of... artificial intelligence we would have to
[00:09:46] what artificial intelligence is because in this case we are mainly referring to large language
[00:09:50] models, to systems like RAG, so these are
[00:09:53] AIs that point to that segment that people are
[00:09:57] looking for, that consumers are looking for,
[00:10:00] in fact in the case of book production there have
[00:10:04] already been cases in which in scientific
[00:10:07] work artificial intelligence promoted
[00:10:10] authors within papers that did not exist, people used
[00:10:14] and cited authors who never existed, they were hallucinations of
[00:10:17] AI, they sounded very real, and when placed in
[00:10:21] Google it seemed they did exist, but they never made it to the paper and it happened. And
[00:10:25] it went through major publishers, but let's remember that the world currently
[00:10:29] also has a consumption pressure, to have
[00:10:32] numbers of which is the most read book, sometimes
[00:10:35] it doesn't matter to reach depth in that sense, many people don't read to reach
[00:10:39] depth, but rather read to accumulate reading, yes, to say well
[00:10:43] I read three papers today, I read three papers tomorrow, I can say
[00:10:47] this in this, I can say this in the other, but not reach depth and that happens
[00:10:51] many times and another thing that is not taken much into account happened before
[00:10:55] artificial intelligence is that on the internet what has more
[00:10:58] consultations is more visible and now with artificial intelligence what has
[00:11:02] more consultations is also more visible because that information is more repeated in
[00:11:06] the training data, it will be more capable of giving us
[00:11:10] authors from other countries than from our region, it will be more capable of
[00:11:14] giving us papers from other countries than from our region, it will also
[00:11:17] be much more efficient in giving you a
[00:11:21] summary of more read books, of more consumed books than of books
[00:11:25] from our countries or our regions, so that also needs to be looked at
[00:11:29] closely, without a doubt, and let's remember we are
[00:11:32] talking about what are
[00:11:36] language models and of course they are algorithms, in some
[00:11:39] cases they mention that it's like the Ouroboros
[00:11:43] which is like a snake that eats itself because
[00:11:48] what these language models have been trained for and the topics
[00:11:52] that are being discussed there, for example Latin American literature, we already
[00:11:56] talked about it before, in Latin American literature maybe you can't
[00:11:59] find something precisely because there isn't, through
[00:12:03] these language models, through this artificial intelligence,
[00:12:06] information about it, right? In what way is this Ouroboros working? How do
[00:12:10] you see it? Language models are trained
[00:12:14] with data. The data comes from how you
[00:12:17] get it on the internet, you get a lot of
[00:12:20] information, we could say Eurocentric
[00:12:24] like papers from recognized scientific
[00:12:27] journals, but not ancestral Latin American knowledge
[00:12:31] or knowledge that is oral, the
[00:12:34] research that is carried out that is not published in these types of journals,
[00:12:38] so by not training artificial intelligences with
[00:12:41] that type of information, they will only answer you with what they were
[00:12:45] trained with and that is lost,
[00:12:48] okay, so that's one
[00:12:51] side with the data that is put in and with what... the
[00:12:55] snake is that as language models are increasingly desired to be made larger and
[00:12:59] larger to handle more and more information, they run out of
[00:13:02] digitized data because that is the other problem that must be understood, that artificial
[00:13:06] intelligence, being algorithms and computers, uses
[00:13:09] digitized data, so the
[00:13:13] same people who train the models have started to
[00:13:15] generate data with the models, so they generate data with
[00:13:19] the models to train models and the data generated
[00:13:22] by humans has been somewhat lost, so
[00:13:26] the models are eating themselves because we are not talking
[00:13:30] about this hallucination that artificial
[00:13:33] intelligence has and that is taken for granted that
[00:13:36] it is a bibliographic reference,
[00:13:39] yes, because artificial intelligence deep down is
[00:13:43] doing, in a very reduced way, generating one word after another through
[00:13:47] a probability, it's like mathematics, it's not
[00:13:50] clarifying and seeing if the phrase it makes is a correct phrase or
[00:13:54] a literary phrase or anything, it just generates the word that makes
[00:13:58] the most sense that comes next and that's why many times it's, since
[00:14:02] it's a probability, there's a high probability that the phrase it's
[00:14:05] generating is a hallucination that it decided
[00:14:08] was the most probable, so they also generate texts with
[00:14:12] hallucinations that are also self-generating to
[00:14:18] the things that is said today is that as
[00:14:21] this race for large language models with a lot of information
[00:14:25] generating data with the same models is
[00:14:28] generating models that are flattening out, they are
[00:14:31] losing, there are even investigations already on the matter,
[00:14:35] there is also the issue of bias, right? Because this can also lead to a
[00:14:38] debate about whether there is bias or not regarding the content that can
[00:14:42] be taken into account
[00:15:28] It's no longer just a test of courage to face a
[00:15:31] risk, another kind of courage is needed, the courage of
[00:15:35] perseverance, the courage of...
[00:15:38] The courage of resistance, it is a significant moral
[00:15:42] problem, it is precisely that which brings
[00:15:45] us closer to the true concept of a revolutionary,
[00:15:48] to the concept of man, and more than of man, of
[00:15:51] a revolutionary, who, as Che said, is the most
[00:15:55] honorable title, the highest rank a man
[00:15:58] can hope for, to be a revolutionary, Fidel
[00:16:02] Castro. November 4,
[00:16:05] 1969, speech delivered at an event
[00:16:08] with members of the Revolutionary Armed Forces, FAR,
[00:16:12] held at the Ministry of the Revolutionary Armed Forces,
[00:16:15] Havana,
[00:16:17] Cuba. Instant news, with a
[00:16:26] complete vision of Latin
[00:16:29] America and the Caribbean, wherever you are, with the Telesur
[00:16:33] app, you have access to live broadcasts,
[00:16:36] exclusive videos and in-depth
[00:16:40] analysis, be part of the community that builds the future of the Global South.
[00:17:25] Thank you for following us in text and context, today talking about
[00:17:28] artificial intelligence, are we reading more with
[00:17:32] AI, are we writing more with AI, that is the question and the
[00:17:35] debate today, María Paula Herrero, professor of the artificial
[00:17:39] intelligence career at the Humberto Fernández Morán University,
[00:17:43] also joined by Lino Meneces from the General Directorate of Artificial Intelligence for the
[00:17:46] bias, in what some say, you also spoke
[00:17:49] about the way it is also affecting the cognitive
[00:17:53] process as well, well, critical thinking, we are
[00:17:57] facing that important debate with artificial intelligence
[00:18:00] taking into account how language models and all
[00:18:04] these applications are allowing, for example, reading a book in 10 minutes.
[00:18:09] Indeed, I believe that artificial intelligence is posing a very
[00:18:13] serious epistemological problem, which could even
[00:18:16] have antecedents in that neopositivist trend of the Vienna
[00:18:19] Circle, when the only thing that mattered was that the protocolary
[00:18:23] statements were logically well articulated, it didn't
[00:18:26] matter if they corresponded to reality or not, in such
[00:18:30] a way that artificial intelligence can build us
[00:18:33] an entire apparent framework that is very
[00:18:36] congruent, but... that does not really correspond to the
[00:18:39] objective world and therefore gives a totally
[00:18:43] biased image of reality. The other element that
[00:18:46] I agree with the professor on is its Eurocentric nature, because
[00:18:50] almost everything is in English first of all. The other is that
[00:18:53] it ignores other types of knowledge and since knowledge must have a
[00:18:57] multifactorial basis, it cannot be determined solely by one
[00:19:01] source, even if artificial intelligence is
[00:19:04] capable of receiving an infinite
[00:19:08] amount of information, even Noam Chomsky says that this
[00:19:12] artificial intelligence is a kind of authorized plagiarism, isn't it?
[00:19:15] Well, it feeds on many sources, but sometimes those sources are not
[00:19:19] reliable, they are totally false, right? And therefore, in this
[00:19:23] era when the so-called post-truth is talked about, which is not such post-truth, it is structured
[00:19:27] lies, I believe that artificial intelligence is posing
[00:19:31] a serious problem to education and scientific research. I
[00:19:34] just gave a conference in Mexico about
[00:19:38] educational technologies, about artificial intelligence and scientific
[00:19:41] leadership in which I raise that. The book
[00:19:45] has just been published in Spain by Dickinson
[00:19:48] because it is a very serious problem for students
[00:19:52] as well as for professors as well as for scientific
[00:19:55] researchers. We are returning to that same
[00:19:58] concern in academia about
[00:20:02] Eurocentrism in all studies, in all
[00:20:05] publications and books that have
[00:20:09] been seen over many decades, that same
[00:20:12] concern is also raised with artificial intelligence and its
[00:20:16] content. I think so, that of course we are
[00:20:20] carrying a whole Eurocentric heritage
[00:20:23] that underestimates these values of indigenous
[00:20:27] peoples, of other forms of knowledge, of other
[00:20:30] emotional, affective, volitional
[00:20:33] elements that make up the contradictory human condition that cannot
[00:20:37] be reduced simply to mathematical algorithms,
[00:20:40] perhaps artificial intelligence is a consequence of that
[00:20:44] hyper-rationalism that has characterized modern philosophy
[00:20:47] from René Descartes to today and that can
[00:20:51] lead us to a dead end of the
[00:20:54] robotization of all educational
[00:20:57] training of new generations and that is
[00:21:01] dangerous, although I repeat, artificial
[00:21:05] intelligence can be used in a very beneficial way and has
[00:21:08] demonstrated an infinite number of potentialities in
[00:21:12] education, but everything depends on how it is used, everything depends on
[00:21:16] how it is used and we talked Lino recently about
[00:21:20] how companies like Anthropic are taking books,
[00:21:24] destroying them and putting them directly
[00:21:28] digitally into a computer in which
[00:21:31] artificial intelligence remains there in a limbo, we don't know what
[00:21:35] it does there to then
[00:21:37] extract information from it, how are you seeing that process, obviously it's a debate that is not
[00:21:41] only happening in countries where artificial intelligence is already being
[00:21:45] cataloged as a superintelligence, but
[00:21:48] also within the United Nations, where we have seen recently the debates that it has been one of
[00:21:52] the central themes, but the way it is destroying books, as we saw
[00:21:56] in recent information and the way it is also
[00:21:59] being used in that sense, how do you see it? Yes, well,
[00:22:02] the topic of Anthropic and books starts from an ethical problem
[00:22:06] from the beginning. In the end, they are buying the books, but the utility
[00:22:10] they need is to fill the model with the largest
[00:22:13] amount of information,
[00:22:16] benefit? What they need is to extract words from the model
[00:22:20] using the professor's words, plagiarism, correct, they
[00:22:24] need those words that are linked to have existed
[00:22:27] before, nothing that AI says is
[00:22:29] totally its own, it already existed somewhere,
[00:22:33] we have the practical example right now with the resolution of
[00:22:37] the millennium problem, yes,
[00:22:40] the resolution of the problem had used artificial intelligence to
[00:22:44] make certain statements
[00:22:47] and the company took
[00:22:50] that chat, because they weren't even public ideas,
[00:22:54] those chats it had with the person, and
[00:22:56] used those ideas to solve the problem before
[00:22:59] them, because it had more computing power, because it's a mathematical problem, and spending
[00:23:03] more money, and spending much more money, yes, of course,
[00:23:06] so authorized plagiarism exists
[00:23:11] AI, all that series of words that are linked
[00:23:14] already existed at some point, that's why the more information it has
[00:23:18] it will answer better, but more information of what we would enter into the
[00:23:21] discussion, what does the company want, because we are talking
[00:23:24] about American companies
[00:23:27] mainly and Chinese open source models, what does the
[00:23:30] company want exactly, to sell you AI, to sell you the answer that AI has,
[00:23:34] to sell you tokens, yes, what generates the answer, so they
[00:23:38] need more information to generate more tokens and make them sound more
[00:23:41] real, and we omit in that process because there is not much
[00:23:45] digitization in our countries, the answers that
[00:23:48] we ourselves have... Now going back a bit to reading
[00:23:52] it leads us to another problem, if
[00:23:54] we start reading only what AI gives us, whether
[00:23:58] in practical cases, in cases of
[00:24:01] makes us reflect and grow as people, then
[00:24:05] we will have another problem that we will not have no we will not
[00:24:09] find answers from our territories, from our
[00:24:12] realities, but we will also start copying,
[00:24:16] importing solutions that appear in the books with which those
[00:24:20] models are trained, which is limited, of course, as we see that and as you mention,
[00:24:23] they need to destroy the books to be able to feed it
[00:24:29] for example in Latin America and the cultural
[00:24:31] richness we have here on the continent is not placed there then
[00:24:35] we are not doing exactly, they are very different realities, the answers of the
[00:24:39] models and one sees them day by day in our jobs, the answers of the models
[00:24:42] are adapted to other realities because they were trained
[00:24:45] with those other realities, when we use it in practical cases of
[00:24:51] retraining, looking for information, training other models
[00:24:54] to be able to adjust to what we need our problems, the resolution of our
[00:24:58] reality, of course, now Maria, uh, taking into
[00:25:01] account this whole scenario, what do you recommend for a
[00:25:05] person who is, of course,
[00:25:08] looking for information, trying to find information in artificial
[00:25:12] intelligence, well, taking into account all these aspects that we have
[00:25:15] maintained, what suggestions can a person have who says, "well, I'm going to look for
[00:25:18] information, maybe it will serve me or not serve me," look,
[00:25:22] I think it's a good
[00:25:25] time to rescue or to start
[00:25:28] working with a lot of force on critical thinking, that
[00:25:31] is, AI is a tool and it is a
[00:25:35] useful tool, the truth is that it helps a lot, but you cannot take what it
[00:25:39] tells you at face value, you have to think,
[00:25:42] analyze, reflect, look for sources, compare,
[00:25:46] this, many people use it as something fast and and so that it...
[00:25:50] fuses everything immediately and
[00:25:54] lies, because in the end it helps you in many things, but it also
[00:25:59] it is giving you is correct, you also have to take into account. that it has a
[00:26:03] bias, sometimes it's not even a geopolitical tool that
[00:26:07] has the bias, it's that the data with which it was trained
[00:26:11] was not sufficient and then this is
[00:26:14] not only the bias of the amount of data but that the data that
[00:26:18] are minority flattens them, removes them because it is not the most
[00:26:21] frequent so well use the tool
[00:26:24] but use it with critical thinking, ask yourself if that is correct, check
[00:26:28] the sources, especially the students, I for
[00:26:32] example. I have no problem with them doing homework using AI, but they have to
[00:26:35] analyze what AI is giving them,
[00:26:38] because it doesn't make sense to grab, copy, paste and deliver, no, because
[00:26:42] besides, the idea is that it is a tool, you also have to learn to
[00:26:46] think and reflect, because if not, we are not going to get anywhere,
[00:26:49] no, where will the new ideas come from, where will the new
[00:26:52] contexts come from, there is a very famous computer scientist,
[00:26:56] Grady Bush, who tells you that AI is not
[00:26:59] inventing anything, everything that is there is human knowledge.
[00:27:02] Do not put an AI only with books from 1800 to see
[00:27:06] if it advances with all the technical
[00:27:10] the human mind so use it but it is
[00:27:13] a tool especially now that there is so
[00:27:17] much publicity and a lot of boom because they are trying to sell it to you as
[00:27:20] a service there is a lot of smoke and one has
[00:27:23] to stop seeing those grandiloquent comments that
[00:27:26] are in the media and and realize that it is a tool
[00:27:30] that will help you, of course. and it is a challenge for students, for
[00:27:34] teachers, for families, obviously in the way, as Professor
[00:27:38] Pablo says, of how it is
[00:27:41] academia, through work, through, for
[00:27:45] example, education, very important also, uh, this
[00:27:48] aspect within artificial intelligence, unfortunately my
[00:27:52] time is up, thank you very much to you, Professor Pablo, thank you very much for your
[00:27:56] time with us, thank you, thank you
[00:27:59] all, so we finish www.
[00:28:02] surtv.net also on telegram the telesur news service 24
[00:28:06] hours a day, so we finish, it will be until a new opportunity, thank you for following us.
[00:28:38] After the triumph of the Sandinista Revolution, Nicaragua
[00:28:41] celebrated its first democratic elections organized by the
[00:28:45] FSLN. With popular support, candidate
[00:28:49] Daniel Ortega obtained a resounding victory,
[00:28:52] despite the opposition boycott and pressure from the United States,
[00:28:56] international observers validated the process,
[00:29:00] consolidating a project focused on social
[00:29:03] justice, literacy and national sovereignty.
[00:29:07] November 4, 1984,
[00:29:10] the FSLN wins the presidential
[00:29:13] elections.
[00:29:17] Plastic arts, literature, cinema and
[00:29:20] more. How much do you know about the contemporary cultural
[00:29:23] scene? Discover the connection between art and
[00:29:27] fiction beyond the conventional. In the company of
[00:29:30] artists who are redefining the multidisciplinary
[00:29:32] field. Neta fiction. The
[00:29:36] cultural magazine that connects you with alternative and emerging
[00:29:40] reality. Grand premiere.
[00:29:43] Saturday. Only on Telesur.
[00:30:15] What makes parents avoid the topic of sexuality with their
[00:30:18] children and what is its consequence?
[00:30:22] And to think that it is too early to talk about sexuality
[00:30:25] is rather based on my fear and my prejudice. And if that leads
[00:30:29] me to silence, then I become an accomplice. The
[00:30:32] lack of sex education that exists in families and in society
[00:30:36] in general, get guidance healthily with
[00:30:39] Aisa García and her guest, Dr. Vicenta
[00:30:43] Hernández,
[00:30:45] Saturday, only.