Skip to main content

UDHR and Alignment


The Universal Declaration of Human Rights (UDHR) is a document that sets out fundamental human rights to be universally protected. Ideally any alignment of AI should use this as the basis for what human values are. The document was written in 1948 as a response to the atrocities of the Second World War. They remain the clearest expression of human values I know. They have failed though in practice, as I can certainly think of many examples where the post war governments, in countries like the UK, have breached most of the 30 articles stated. 

If governments can't or won't follow and uphold 30 basic principles for human values, why is there an expectation that AI can or will be able to?

Cansu Canca considered this issue in a post from 2019 "AI & Global Governance: Human Rights and AI Ethics – Why Ethics Cannot be Replaced by the UDHR" Canca states that 'When we dive deep, the UDHR is simply unable to guide us on those questions. Solving such challenges is the job of ethical reasoning.'

The conclusion of: 'I do not mean to say that the UDHR is not of any use in the discussion of ethical tech. Its clarity, legacy, and wide acceptance makes the UDHR a good tool to use to start the exploration on what might be problematic about any given AI system or practices in developing these systems. However, if the aim is not just to identify the problem but also to solve it, then the UDHR is simply inadequate to do so. Here, I invite you to engage in ethics.'


Comments

Popular posts from this blog

The AI Dilemma and "Gollem-Class" AIs

From the Center for Humane Technology Tristan Harris and Aza Raskin discuss how existing A.I. capabilities already pose catastrophic risks to a functional society, how A.I. companies are caught in a race to deploy as quickly as possible without adequate safety measures, and what it would mean to upgrade our institutions to a post-A.I. world. This presentation is from a private gathering in San Francisco on March 9th with leading technologists and decision-makers with the ability to influence the future of large-language model A.I.s. This presentation was given before the launch of GPT-4. One of the more astute critics of the tech industry, Tristan Harris, who has recently given stark evidence to Congress. It is worth watching both of these videos, as the Congress address gives a context of PR industry and it's regular abuses. "If we understand the mechanisms and motives of the group mind, it is now possible to control and regiment the masses according to our will without their...

A Network Analysis Tool to help identify structural gaps

  InfraNodus is a web-based open source tool and method for generating insight from any text or discourse using text network analysis. The byline on the website states, 'Get an overview of any discourse, reveal the blind spots, enhance your perspective.' which, whilst accurate does little to summarise the potential of such a tool. Watching the introduction helps. Its capabilities include representing any text as a network and identifying the most influential words in a discourse based on the terms' co-occurrence, providing text network visualization and analysis live as new data is added, offering discourse structure analysis to measure the level of bias in discourse and identify structural gaps in discourse, and being available via an API to be used in conjunction with other text mining and analysis software. The white paper, ' Generating Insight Using Text Network Analysis ' concludes:  'The tool is currently used by researchers, marketing professionals, stude...

CRM and AI?

Artificial intelligence (AI) can be used in a CRM system to enhance customer service, sales performance, and marketing strategies. Here are some examples of how AI can be applied in a CRM: - AI can enable natural language processing and voice input, such as Siri or Alexa, to allow a CRM system to answer customer queries, solve their problems, and even identify new opportunities for the sales team. Some AI-driven CRM systems can even multitask to handle all these functions and more. - AI can help with sales forecasting by analysing historical data, customer behaviour, and market trends. This can help the sales team make more accurate predictions for future sales figures and determine a success metric. - AI can assist with lead management by automating the process of qualifying and nurturing prospects. It can use chatbots and email bots to understand leads' needs and inform the sales team to improve their performance. With insights gained from these bots, companies can optimise their...