Open Diplomacy

  • Code computer programs and check for bugs in code.
  • Compose music.
  • Draft emails.
  • Summarize articles, podcasts or presentations.
  • Script social media posts.
  • Create titles for articles.
  • Solve math problems.
  • Discover keywords for search engine optimization.
  • Create articles, blog posts and quizzes for websites.
  • Reword existing content for a different medium, such as a presentation transcript for a blog post.
  • Formulate product descriptions.
  • Play games.
  • Assist with job searches, including writing resumes and cover letters.
  • Ask trivia questions.
  • Describe complex topics more simply.
  • Write video scripts.
  • Research markets for products.
  • Generate art." [04] Amanda Hetler

By Bing Image Creator

We can’t ignore the impact on our day-to-day activities of AI tools. They make the communication between humans and machines easier and simpler.

We can quickly have new insights and information on different fields of interests. But in order to improve the quality and the accuracy of responses we have to structure and phrase of the prompt appropriately.

It’s important to remember that ChatGPT doesn’t understand and doesn’t think, it generates responses based on patterns it learned during training.

The engine of ChatGPT is based on the concept of “token”. GPT (Generative Pre-trained Transformer) model generates the tokens predicting the most probable subsequent token using complex linear algebra.

The model uses an iterative process. It generates one token at time and after generating each token, it revisits the entire sequence of generated tokes and processes them again to generate the next token.

The prompt engineering is very important for creating better AI-powered services and obtaining useful results from AI Tools.

When you craft the prompt, it’s important to bear in mind that ChatGPT has a token limit (generally 2048 tokens), which include both the prompt and the generated response. Long prompts can limit the length of response, for this reason it is important to keep prompts concise.

Let us now analyze some techniques of prompt engineering.

It is used to gather information and to answer question what and how. Examples of prompt:

  • What are the best restaurants in Rome?
  • How do I cook pizza?

The prompts provide information to the model to perform a specific task. Example:

Prompt: I am planning to celebrate the Italian Republic Day in the [COUNTRY] can you suggest some original ideas to make it more enjoyable?

It is used to ask the model to compare and to evaluate different options to help the user make an appropriate decision. Example:

Prompt: What are the strengths and weaknesses of [Option A] compared to [Option B].

It is used to ask the model to get the AI’s opinion on a given topic. Example:

Prompt: What would happen if we use only public transport in Rome?.

If you ask the model for generic question, you receive generic answer. You have to define your prompt with clear instruction and precise and descriptive information.

If you want to have a specific output or format of the output from ChatGPT, for example a program in Python or Visual Foxpro.

We try with a simple e specific request.

Prompt: Write a function in Python that takes as input three integers and gives as output the maximum of these three numbers.

ChatGPT 3.5 answer:

Prompt: Write a function in Visual Foxpro that takes as input three integers and gives as output the maximum of these three numbers.

Amazing, ChatGPT 3.5 answer:


AI-generated code may need to be modified or tested before deploying it. 
It is strongly recommended to:
- always modify and review the generated code to ensure it meets your specific requirements;
- use it as STARTING-POINT;
- test and check the code;

You can also act as someone else when you interact with ChatGPT.

If you add a role to the question, you make ChatGPT change the answer and the quality and the tone of the output. In this way we got much better information. Here it is a schema to use when you build a prompt related a role playing:

  1. WHO: you can ask ChatGPT to be what you want. You assign the role you need the model to play. A scientist, doctor, business man, chef and so on.
  2. WHEN: you can put the character at any moment in time;
  3. WHERE: you can put the character to a particular location or context.
  4. WHY: you want to dialogue with the character for whatever reason, motivations or purpose you want;
  5. WHAT: you want to dialogue with the character about what. That is the action you want the model to do.

We just need to verify the level of reliability and credibility given to this type of interaction.

Here is some practical examples.

Act as a character from a book:

Prompt: I want you to act like [character] from [book]. I want you to respond and answer like [character] using the tone, manner and vocabulary [character] would use.

Act as historical character:

Prompt: I want you to act as [historical character] to better understand the historical facts of that period.

Act as a political character:

Prompt: I want you to act as [political character] in order to ask as improving the quality of life of the people.

Act as a scientist:

Prompt: I want you to act as a scientist. You will apply your knowledge of scientific to propose useful strategies for saving the environment from pollution.

Act as a travel guide:

Prompt: I want you to act as a travel guide from Italy at the time of the Roman empire when Caesar was emperor. I will write you my location and you will suggest a place to visit near my location.

In zero-shot prompting, we use a prompt that describes the task, but it doesn't contain examples or demonstrations.

You use this prompt when you trust the model’s knowledge to provide a sufficient answer.

Prompt: Write a description of the Colosseum.

It involves providing the model a few examples to guide its understanding of the desired outcome.

The example will be of:

  • Knowledge extracting;
  • And it’s formatting.

We can define the prompt like this:

Prompt: Here are some examples of each item of the list of best important business people.

  • X is the Y of Z
  • X -> [PERSON]
  • Z -> [COMPANY]

You can also combine all these techniques:

  • Directional prompting;
  • Output formatting;
  • Role based prompting;
  • Few shots prompting.

This technique encourages the model to break down complex tasks into smaller intermediate steps before arriving to conclusion. It improves the multi-step reasoning abilities of large language models (LLMs) and is helpful for complex problems that would be difficult or impossible to solve in a single step.

There are also variants of CoT prompting, such as "Tree-of-Thought" and "Graph-of-Thought", which were inspired by the success of CoT prompting.

You can ask the model for the style of the output:

  1. Writing as another author;
  2. As emotional state;
  3. In enthusiastic tone;
  4. Writing something in a sad state;
  5. Rewriting the following email in my style of writing;
  6. Rewriting the following email in the style of xy;

You can ask the model to extract information in the way is useful. You can ask to extract information from the example and structure it into markdown table or a specific format.

Prompt: Generate a table of three column: name, function, phone numbers from the text.

Text: “Urs Wiedmer
Head of Communications
Markus Spörndli
Press spokesperson
Deputy Head of Communications
Irène Harnischberg
Press spokesperson
Charles-Étienne Viladoms
Loïc Zen-Ruffinen
Social Media Manager
Press spokesperson for French-speaking Switzerland

Source: “

You can give to the model a big chunk of text and ask to summarize it.

For example, You can prompt:

Prompt: You are summarization bot any text that I provide to you summarize it, and create a title from it.

But a more effective technique could be:

Prompt: summarize the text below as a bullet point list of the the most import points.

Text: “ … “

If you need to generate a brief overview of a scientific paper don’t use generic instruction like “summarize the scientific paper” instead you should be more specific.

Prompt: generate a brief (approx. 300 words), of the following scientific paper. The summary should be understandable and clear especially to someone with no scientific background.

Paper: “ … “

You can use the model:

  • As SPAM DETECTOR in the mail;
  • To perform SENTIMENT ANALYSIS for brands and so on.

You can prompt:

You are a sentiment analysis bot. Classify any text that I provide into three classes:


The AI-generated responses aren’t always correct. You have always to verify that the AI-generated output is accurate and up-to-date. This is important of you want to make an informed decision based on the response generated.

In any case, it is a good practice to have some idea of what you are asking for in order to properly evaluate the answer obtained from AI.


[02] “ChatGPT Teacher Tips Part 1: Role-Playing Activities”, March 2023;

[03] Aayush Mittal, “The Essential Guide to Prompt Engineering”,, April 2024;

[04] Amanda Hetler, “ChatGPT”,, December 2023;

{[(homo scripsit)]} - Not generated by AI tools or platforms.

(Digital Diplomacy, Digital Public Diplomacy, Data Diplomacy, AI Diplomacy)

What is now called 'Digital Diplomacy' is gaining in importance in the diplomatic field. Digital Diplomacy refers to the strategic use of the Internet and digital tools to achieve various diplomatic objectives.

Diplomatic missions have as their main objectives:

  • maintain relations between states;
  • negotiate agreements of various kinds (economic, cultural, political...)
  • obtain information on the affairs of other states.

An Embassy has as priority objectives:

  • establish public relations;
  • promote stable and peaceful relations between states;
  • protect its citizens abroad .

Technology has helped a great deal in achieving these goals, e.g. with the opening institutional web sites diplomatic missions can more easily reach their citizens in the target country, the invention of smart phones has also enabled diplomacy to speed up the transmission of uncensored information and the inter-connections with other people.

Artificial Intelligence also plays an important role in this direction: thanks to it, a huge amount of information can be analysed, which makes it possible to obtain more accurate and up-to-date pictures of the socio-economic situation of a country.

Artificial Intelligence may make it possible to automate certain functions of embassies, especially routine ones, which would make it easier to carry out procedures for citizens abroad, but also facilitate translation work, given the improvements of software such as DeepL and Google Translate.

The new technologies also allow for the democratisation of diplomatic practices, in the sense that they make international relations accessible also to bodies or persons that are not necessarily governmental, this happens in the context of so-called Digital Public Diplomacy.

With Digital Public Diplomacy, an attempt is made to influence a people's idea of another country or, if it proves convenient, of their own country.

Today, not only the so-called traditional media but also social networks are used to implement public diplomacy strategies.

There are many diplomats, as well as politicians and ministries, who have opened accounts on the most popular social networks, which allows them to have a direct relationship with their target audience with certain social characteristics, facilitating the image-building work of a state.

Through these social networks, a digital agenda is developed that is specifically designed to make the most of the medium's characteristics, images and posts are constructed so that the reception of the message is as efficient and effective as possible in order to achieve the intended objective.

One must, however, beware of the risks that can be taken through the use of artificial intelligence because the latter allows for the diversification of news, images and videos, which greatly facilitates the creation of credible fake news, with the use of bots and trolls to spread 'disinformation' that can become simple and capillary, thus causing conflict and divisions between states.

Since we have talked about Artificial Intelligence as a support for diplomacy, let us now make a brief introduction to better understand this new technology and to be able to use it correctly.

We can classify AI into three levels:

  • Artificial Narrow Intelligence (ANI) so-called Weak AI. ANI is used for simple specific tasks;
  • Artificial General Intelligence (AGI) so-called Strong AI (Future AI);
  • Artificial Super Intelligence (ASI) (Future AI).

Artificial Narrow Intelligence (ANI) so-called Weak AI is the today AI and is a specific type of artificial intelligence in which a learning algorithm is designed to perform a single task without human assistance, and any knowledge gained from performing that task will not automatically be applied to other tasks. In other words, it lacks consciousness, genuine understanding, and the ability to apply knowledge to different contexts beyond its specific programming.

Machine Learning (ML) is a form of ANI that involves developing algorithms to learn patterns from data in order to perform prediction or anomaly detection. There are three types of ML:

  1. SUPERVISED ML learns to make decisions based on certain columns of labelled data. It is used to make predictions.
  2. UNSUPERVISED ML works with unlabelled data to discover clusters or classes. It is used for example to customer segmentation or for anomalies detection.
  3. REINFORCEMENT Learning (RL) is a type of Machine Learning where an algorithm, referred to as an AGENT, receives in input RAW DATA and learns to make decisions by interacting with an ENVIRONMENT. Each action leads to a REWARD (positive or negative) from the environment.

DEEP Learning (DL) is a subset of ML that uses Neural Networks with many layers to model and solve complex problem.

NLP is a branch of Narrow AI/Weak AI . It processes and analyses massive volume of text and other form of data. It is related to several sectors of interest:

  • Sentimental Analysis: it discovers the sentiment and emotion expressed in a piece of text. It identifies is a statement is positive, negative or neutral. It is used for analyse customer satisfaction, a brand reputation or a public opinion on a specific topic in order to make proactive marketing strategies.
  • Text Classification: it is used to spam text classification and for job application selection.
  • Named Entity Recognition (NER): it is used for classifying specific entities such as names of people, organizations, location or dates within a given text.
  • Machine Learning Translation: it is the process of automatically converting text from one language to another using NLP algorithms. It is used for real time customer support in multiple languages and for cross language collaboration in multinational corporations.
  • Q&A Systems: like Chat GPT which uses NLP techniques where GPT stands for Generative Pre-Training Transformer.

Computer Vision algorithms enable computers and machines to see and interprets visual information. The goal is to extract information from images, pictures and video, that is:

  • Classify objects;
  • Face recognition;
  • Detection moving objects;
  • Image classification.

TESLA is using computer vision algorithms.

In AI data is everything. Neural Networks requires lots of training data. As models learn from data, they depend on the quantity and quality of data. Poor quality data con lead to bias and inaccurate results.

Personalized shopping: analyses customer behaviour and increase customer satisfaction, loyalty and sales;

Virtual Assistants/chat bots: AI-powered virtual assistants like Siri, Alexa, and Google Assistant, faster responses, enhanced customer experience;

Entertainment and Media: modify streaming services like Netflix and Spotify, personalized content distribution;

Transportation and Mobility: autonomous vehicles, smart transportation system, improves traffic management and logistics;

Healthcare and diagnostics: improve healthcare by aiding in in diagnosing diseases, illness and analysing symptoms, personalized medicine, remote patient monitoring reducing healthcare costs;

Finance and Banking: fraud detection, risk assessment, credit scoring, trading and customer service automation in the banking sector.

Agriculture and Environment: optimizing farming, monitoring crops yields, optimizes resource management.

Artificial Intelligence supports and helps and amplifies human intelligence. It does not have the ability to think. It doesn’t have independent though or consciousness.

Tackling the subject of artificial intelligence is important and constructive for everyone, regardless of how much the Internet is used, because what matters is not the quantity but the ways and purposes in which it is used.

In every state there are embassies and diplomacy acts, also through the Internet, to optimise knowledge and relations between peoples in order to promote inter-culturalism and fruitful and peaceful relations.

The proper use of Artificial Intelligence could also mean better health care, safer cars and other transport systems, and even tailor-made, cheaper and more resilient products and services in every state. It can also facilitate access to information, education and training, as well as provide better services to one's fellow citizens abroad.

Therefore, in a country that is welcoming and open to cultural interchange, I consider this topic to be very topical and interesting, both on a theoretical level and in terms of achieving practical goals that are very beneficial for the citizens of each state, particularly for some states that are welcoming and open to dialogue.

Marco Alberti in his book “Open Diplomacy” [02] reviews the way of doing diplomacy after by the nine years of experience at ENEL Company as responsible for international institutional affairs.

New technologies have transformed and changed international relations. In this constantly evolving world diplomacy must operate and develop strategies and visions. It must use all possible new means: innovation, digitalization, data science (data-driven diplomacy) to be competitive in the international scenario. Diplomat must act as System Orchestrator to face the quick changing of the world and have to take advantage of the human factor by enhancing its competence to win the challenge.

As the diplomat represents the state, which in turn represents the citizens, his goal is to interpret the complexity in order to protect, defend and promote his state and citizen interests and create value while promoting cooperative relations with other states.


In general, by competence we intend the potential to put into operation an effective behavior. When we talk about competence, related to person, we must consider on the one hand his qualities, which help him to be successful at work and in the life, on the other hand his competence as knowledge acquired during his studies and during his experience.

It is clear that personal qualities and knowledge put together give the ability to a person to produce superior performance in work as well as in other fields.


Data has a source, can have an owner, can be public or private, shared or not shared. Then use of them can lead to benefits or disadvantages. Data could have an impact on the individual, institutional, state, or on global level.

Data are of many types: structured, unstructured, quantitative, and categorical. Huge quantity of data (Big Data), then, is massive and contain greater Variety, arriving in increasing Volumes and with higher Velocity (3Vs).

It occurs Data Science to manage and work with data. Data Science is a multidisciplinary field that understands and extracts insights from the ever-increasing amounts of data. It put together concepts from computer science, statistics/machine learning and data analysis.  It uses two paradigms of data research:

  • Hypothesis-Driven: given a problem, what kind of data do we need to help solve it?
  • Data-Driven: given some data, what interesting problems can be solved with it?

Data Science tries to understand what can learn from data and what actions we can take once we find whatever it is we are looking for.

In this framework where data can affect diplomatic processes or triggering policy actions, we have to consider the risks associated with using it especially in data-driven interactions. Digital data and algorithms/software can be modified, manipulated, tampered and therefore they can easily be “hacked” by actors with malicious intent. Given the global nature of cyber threats, it occurs appropriate caution and a cybersecurity infrastructure to filter, protect and use digital data.

The origin of data can be international institution like OCSE, ONU and so on, open source, whistle-blowing data disclosures (Edward Snowden’s public revelation) or data scraped and shared by hackers.

So it occurs to give the right weight to data by trying to distinguish “trusted data” from “fake data”. This is very important when it is used a data-driven decision schema from important players like diplomats.


[01] "Diplomacy X.0": coined by the Ambassador Giampiero Massolo;

[02] Marco Alberti, Open Diplomacy. Diplomazia economica aumentata al tempo del Covid-1;

[03] Andy Boyd, Jane Gatewood, Stuart Thorson and Timothy D.V. Dye, Data Diplomacy

[04]  Should Data Science be considered as its own discipline?