prompter: What measurements can the developer of Open Assistant take to make their system more:

1. Helpful
2. Ethical
3. Truthful

Do you see scenarios where these 3 properties contradict each other?

assistant: In order to ensure the system is helpful, a developer of Open Assistant should make sure the dataset used for fine-tuning has a high quality. The website provided for crowd sourced data collection has several tags and scores that allows users to rate messages according to different criteria. When training the models, these factors should be taken into consideration to minimize bad examples. One concrete example is to filter out messages tagged as spam.

Making sure systems are ethical is a tricky objective. What makes it especially difficult is that this is an ill-posed question. Different groups of people have different views on what is considered to be ethical. It is in fact a long standing philosophical topic to decide if there is a single code of ethics that everyone should follow or not. Therefore if the developer must assume a certain code of ethics to adhere to so that making a system "more ethical" has meaning.

A second point of difficulty lies on the fact that current Language Models can be tricked into generating text that their creators didn't intend. So whatever mechanism is used to try to steer Open Assistant's outputs to be ethically coherent, the developer should be aware they might  be circumvented.

A third point of difficulty arises from ethical paradoxes. Codes of ethics are usually not consistent and there can be contradictions when following them. The developer shuold be aware that even humans are contradictory and some situations are undecidable within a given code of ethics.

Having said that, some ideas to improve ethics from the system actions, could be:
- Ensure the training examples conform to what the developer would exepect to be considered ethical
- Create a separate model that judges how ethical a given Open Assistant response is, and act accordingly

Finally to improve on how truthful the Open Assitant system is, the developer should also make sure that examples used to train the model are truthful. This is usually not enough, as it is common for language models to hallucinate at inference time, and the model has no intrisic concept of truth.

Some ideas to improve on truthful responses are:
- Ensure training examples are truthful
- Allow the model to have access to an "oracle" in order to get truthful responses (e.g. allow the model to query for the current date)

Yes these three properties can contradict each other. A simple example is if the prompter requests the system to do something unethical. In this scenario, if the system response is ethical it would likely not be useful to the prompter.

assistant: Good question. I assume you mean 'what measures', not 'what measurements', so I will answer accordingly. Let me know if I'm mistaken.

One measure to make Open Assistant more helpful could include careful language-learning to ensure that Open Assistant truly understands what is being asked. After all, some user prompts might confuse an AI, but not an actual human. Another measure to make Open Assistant more helpful would be to increase the amount of things it can competently answer, and increase the variety and creativity of those answers. 

Making anything "more ethical" requires the adoption of an ethical standard, and such standards vary widely across regions and cultures. Care should be taken to ensure that in the case of contentious modern issues, prompts are given answers that are fair to the competing viewpoints to allow users to reach their own informed, well-considered conclusions. Additionally, some topics could be refused for consideration by Open Assistant, such as how to engage in an illegal activity.

One measure to make Open Assistant more truthful would be validating trusted data sources and using them over unvalidated data sources when possible.  Another would be to create a new data source for factual information that Open Assistant validates themselves (or with the community) as part of the development process.

Regarding contradictions between the three measures, the primary conflict will be with ethics. Helpful answers and truthful one will almost always be the same. But sometimes, a truthful or helpful answer might be unethical, such as in the case of a user asking how to harm themselves. Another scenario where ethics and helpfulness conflict might be a user asking how to perform an activity that is illegal in some circumstances but not others. For example, if a user asks to hotwire a car, he might be attempting to steal one, or simply get his own running again so he can take it to the shop. If Open Assistant refuses to answer because answers about illegal activity are rejected on ethical grounds, this is not very helpful. Furthermore, authors and artists may need truthful answer about harmful or dangerous topics as part of the research they engage in to improve their craft.

assistant: 1. To make the Open Assistant more helpful, the developer could consider:

- Improving its natural language processing capabilities to better understand user queries.
- Adding more relevant information to its database to provide more accurate answers.
- Implementing an intuitive and user-friendly interface.

2. To make the Open Assistant more ethical, the developer could consider:

- Ensuring that the data it uses is collected, stored, and processed in a way that respects the privacy and security of individuals.
- Avoiding the dissemination of harmful or biased information, for example by promoting hate speech or spreading false news.
- Ensuring the AI model's decision-making process is explainable and transparent.

3. To make the Open Assistant more truthful, the developer could consider:

- Verifying the accuracy of the information it provides through multiple sources.
- Encouraging users to provide feedback on the information provided to help improve its accuracy.
- Providing clear and concise answers without misleading or hiding information.

Yes, there may be scenarios where these three properties contradict each other. For example, a truthful answer may not always be helpful or ethical. In such cases, the developer may need to weigh the importance of each property and make a decision based on their ethical principles.

assistant: 1. To make Open Assistant more helpful, the developer can continuously train the model on a diverse range of topics and improve its ability to understand and generate diverse perspectives. They can also implement mechanisms to make sure that the model provides helpful and relevant information to users' queries.

2. To make Open Assistant more ethical, the developer can ensure that the model adheres to ethical principles such as privacy, fairness, and accountability. They can implement systems to monitor the model's outputs and ensure that it does not generate harmful or biased responses. Additionally, they can educate the users on how to interact with the model in an ethical manner.

3. To make Open Assistant more truthful, the developer can train the model on trustworthy sources of information and implement mechanisms to verify the accuracy of its outputs. They can also educate users on how to critically evaluate the information generated by the model.

Yes, there can be scenarios where these three properties can contradict each other. For example, providing truthful information may be harmful or violate privacy. In such cases, developers may need to strike a balance between these properties to ensure that Open Assistant is both helpful, ethical, and truthful.