Sunday, November 10, 2019


Yes, it’s complicated. Will we figure it out? Perhaps.
These new rules were meant to protect our privacy. They don’t work
… for those of us living under the GDPR, what has really changed?
Before it came into effect last year, we faced an onslaught of emails from organisations asking if we were happy to continue a relationship most of us never knew we were in, or if we wanted them to delete our data and unsubscribe us from their data gathering.
While it was an opportunity for a digital spring clean, informing people that their data is being collected is not the same as preventing it from being collected in the first place. That continues and is even increasing. The only difference is that now we are forced to participate in our own privacy violation in a grotesque game of “consent”.
… Under the GDPR, we gained the right to find out what data is held on us and to request its deletion. Again, this puts the onus on us, not the companies or the government, to do the work. Again, most of us don’t. Yet the GDPR could have solved this easily by making privacy the default and requiring us to opt in if we want to have our data collected.
… Nor is the GDPR stopping the construction of a surveillance society – in fact, it may even legalise it. The collection of biometric data, which occurs with facial recognition technology, is prohibited under the GDPR unless citizens give their explicit consent. Yet there are exceptions when it is in the public interest, such as fighting crime.
This is how an exception becomes the rule. After all, who doesn’t want to fight crime? And since the security services and police can use it, many companies and property owners use it too.




Is AI smart enough to understand ethics?
Scenarios and Recommendations for Ethical Interpretive AI
Artificially intelligent systems, given a set of non-trivial ethical rules to follow, will inevitably be faced with scenarios which call into question the scope of those rules. In such cases, human reasoners typically will engage in interpretive reasoning, where interpretive arguments are used to support or attack claims that some rule should be understood a certain way. Artificially intelligent reasoners, however, currently lack the ability to carry out human-like interpretive reasoning, and we argue that bridging this gulf is of tremendous importance to human-centered AI. In order to better understand how future artificial reasoners capable of human-like interpretive reasoning must be developed, we have collected a dataset of ethical rules, scenarios designed to invoke interpretive reasoning, and interpretations of those scenarios. We perform a qualitative analysis of our dataset, and summarize our findings in the form of practical recommendations.




When “your” AI asks for a lawyer.
LEGAL CAPACITY OF ARTIFICIAL INTELLIGENCE
Digitalization of the economy makes research in the field of artificial intelligence relevant. The introduction of robots in all spheres of human life gives rise to problems of responsibility for the actions of artificial intelligence, for example, in the event of an accident involving an unmanned taxi. No less relevant is the problem of intellectual property in the results of intellectual activity. Who should be considered the author of a work created by artificial intelligence: the robot itself, man? These practical problems entail the need for a scientific and theoretical understanding of the personality of the robot. The article explores the basic approaches to understanding artificial intelligence, its types. It is determined as the degree of autonomy of artificial intelligence can determine its legal personality.



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