The problems of the Argentine economy and their solutions, according to ChatGPT
The web is currently enabling the use of an advanced artificial intelligence model called OpenAI’s GPT-3 (https://chat.openai.com). The page or model answers various questions and demands that may be presented, such as generating a film script, describing an event or a historical figure, or clarifying existential doubts.
Ultimately, after consulting the information available on the web, it offers us a synthetic answer, something like an elaborated consensus of the available information. Consequently, his texts cannot be surprising or new, although the perfect writing and presentation of the answers are striking. We did the experiment of demanding information about the main problems of the Argentine economy, and this was his diagnosis:
Inflation is the main problem, a phenomenon that characterizes the Argentine economy throughout its history. The continuous increase in prices erodes purchasing power and makes it difficult for consumers and businesses to make appropriate decisions over time.
The value of the Argentine currency fluctuates dramatically, increasing the cost of imports and making it difficult for entrepreneurs to compete in the global market.
The Huge public debt impedes spending on infrastructure and social goals.
Corruption is widespread, affecting both the public and private sectors and undermining trust in government institutions.
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What are the solutions to improve this disaster?
First, concentrate public spending on priority objectives, reducing subsidies and transfers. Also, control spending on public salaries and the outlays of the retirement system. On the other hand, productivity must be increased, and investment encouraged, generating a stable macroeconomic environment, which includes a free exchange rate.
The answers that this artificial intelligence model gives us are quite obvious. However, they are useful since Argentines characterize themselves by not applying economic policies that anywhere in the world would be considered absolute common sense.
So, this clear answer raises a new question: what are the reasons why we Argentines could not solve these problems through effective policies?
When making the query, the respondents pointed to a broad set of historical, social, and political factors and the productive structure. More in detail, among the determinants, is the history of crises that have contributed to a loss of confidence, economic inequality that reduces the capacity of the State to face economic challenges, and political polarization that hinders the implementation of effective and sustainable policies. The trained model also targeted natural resource dependency and cultural factors. Additionally, he highlighted the importance of sustainability and broad consensus.
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At the end of the dialogue with the chat, we refrained from asking him about the future for two reasons. First of all, we understand that this algorithm is, in its essence, simply a mechanism that summarizes the documents with which it was trained. It is not a model that represents the world and draws new conclusions based on this representation. Second, the model is not enabled to generate answers about the future.
In this way, the interview leaves us with a message with contrasts. On the one hand, a diagnosis of our difficulties is proposed with specific recommendations to solve the problems. In other words, a well-defined roadmap emerges.
However, in trying to explain our painful trajectory with persistent setbacks, the algorithm identifies a set of determinants that would have prevented effective policy implementation. According to this summary, the outlined roadmap was implemented in a terrain full of obstacles resulting from social, political, historical, and cultural traits. Therefore, we need both a good roadmap and the ability to overcome obstacles.
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