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Where a regular algorithm perceived a group of people standing around a window as just that, Norman saw them as potentially jumping out of the window. This experiment shows how training data can be highly influential in establishing biases, resulting in potential AI decisions that we could not explain given our limited ability to understand how such biases were formed. These biases are already present in algorithms that disproportionately target people based on race as being at risk for recurring criminal offense.
A recent paper also found examples of racist and sexist language in a large, and massively popular, machine learning dataset. It is inevitable that AI will be subject to all sorts of biases based on the training data that it is exposed to, just like we humans are subject to the biases of the cultures in which we were raised.
One of the challenges of establishing an AI code of ethics is determining whose ethics we should use. A study has shown that, in the example of an autonomous car having to make a decision as to whether to kill a child or a grandparent, the ethical decision would vary depending on where you are from.
In response to the black box problem - the fact that we will not always know how AI derives its conclusion - is it possible to limit the bias the AI is subject to by exposing it to a large variety of datasets? Would it be best to train the AI with multinational and multicultural data in order to avoid our own human biases influencing its decisions?
Is it possible to establish norms of how AI should be trained? Daniel Dennett, a renowned philosopher and cognitive scientist suggests that a natural part of the evolution of intelligence itself is the creation of systems capable of performing tasks their creators do not know how to do. There are indeed many unanswered questions. The sooner we start searching for answers the higher the likelihood of a positive outcome.
The Dilemmas of Wonderland: Decisions in the Age of Innovation
Recommended Reading:. Driving a car requires judgments in multiple situations impossible to anticipate and hence to program in advance. What would happen, to use a well-known hypothetical example, if such a car were obliged by circumstance to choose between killing a grandparent and killing a child? Whom would it choose? Which factors among its options would it attempt to optimize?
And could it explain its rationale? Recent Posts See All.
Difficult Decisions: A Tool for Care Workers Managing Ethical Dilemmas | GNP+
You're in preview mode. When a driver slams on the brakes to avoid hitting a pedestrian crossing the road illegally, she is making a moral decision that shifts risk from the pedestrian to the people in the car. Self-driving cars might soon have to make such ethical judgments on their own — but settling on a universal moral code for the vehicles could be a thorny task, suggests a survey of 2.
For example, in a scenario in which some combination of pedestrians and passengers will die in a collision, people from relatively prosperous countries with strong institutions were less likely to spare a pedestrian who stepped into traffic illegally.
Decisions and Dilemmas: Case Studies in Presidential Foreign Policy Making Since 1945
Respondents were asked to choose who to spare in situations that involved a mix of variables: young or old, rich or poor, more people or fewer. People rarely encounter such stark moral dilemmas, and some critics question whether the scenarios posed in the quiz are relevant to the ethical and practical questions surrounding driverless cars. They argue that the findings reveal cultural nuances that governments and makers of self-driving cars must take into account if they want the vehicles to gain public acceptance. At least one company working on self-driving cars — the German carmaker Audi — says that the survey could help prompt an important discussion about these issues.
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Other firms with autonomous-vehicle programmes, including auto manufacturer Toyota and technology companies Waymo and Uber, declined to comment on the findings. Many of these companies argue that the vehicles could improve road safety, ease traffic and improve fuel efficiency. Social scientists say the cars raise ethical issues, and could have unintended consequences for public safety and the environment.
Curious to see if the prospect of self-driving cars might raise other ethical condundrums, Rahwan gathered an international team of psychologists, anthropologists and economists to create the Moral Machine. Within 18 months, the online quiz had recorded 40 million decisions made by people from countries and territories. No matter their age, gender or country of residence, most people spared humans over pets, and groups of people over individuals.
Research tests how people make moral decisions using classic dilemmas
These responses are in line with rules proposed in what may be the only governmental guidance on self-driving cars: a report by the German Ethics Commission on Automated and Connected Driving. But agreement ends there.
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When the authors analysed answers from people in the countries with at least respondents, they found that the nations could be divided into three groups. One contains North America and several European nations where Christianity has historically been the dominant religion; another includes countries such as Japan, Indonesia and Pakistan, with strong Confucian or Islamic traditions.
Decisions and Dilemmas I. Learning About the European Union from a Historical Perspective The project Decisions and Dilemmas: Learning about the EU from a historical perspective engages a cross-border and mixed group of academics and school educators in the fields of history and citizenship into the collaborative development, testing and implementation of online cross-border educational modules for both history and citizenship at secondary school level.
Project Aims To promote competence-based, learner-centred, multiperspective approaches to history and citizenship education, in a way that shows the relevance and significance of learning about the EU nowadays To make students understand the changing context in which the European Institutes operates. Latest news. A Historiana Project. Project managers.