Law
Checks and balances in AI ethics
Ethics of AI: While artificial intelligence promises significant benefits, there are concerns it could make unethical decisions. Prefer to listen to this story? Here it is in audio format. Artificial intelligence (AI) is fast becoming important for accountants and businesses, and how it is used raises several ethical issues and questions. While autonomous AI algorithms teach themselves, concerns have been raised that some machine learning techniques are essentially "black boxes" that make it technically impossible to fully understand how the machine arrived at a result. It will become increasingly important to develop AI algorithms that are transparent to inspection, auditable, secure and robust against manipulation and misuse.
Over 100 people held for unauthorized drone flights in Japan in 2019
Japanese police arrested or took other action against 115 people for civil aviation law violations linked to unauthorized drone flights in 2019, up 31 from the previous year, government data showed Thursday. The National Police Agency tally included 51 foreign nationals, of whom 19, the largest group, were Chinese. Seven were from the United States. Last year, the number of cases that led to police actions stood at 111. Of them, 54 cases happened as offenders tried to take commemorative pictures, while 34 cases were flight operation exercises, according to the NPA data.
Artificial intelligence and the regulatory landscape Lexology
Currently, the European Union does not have any specific legislative instrument or standard to regulate the use and development of AI. However, these requirements are likely to set the stage for future legislation, similar in scope and effect as the General Data Protection Regulation (GDPR) for privacy, therefore indicating that the European Union may be on the cusp of providing for specific and unique AI regulatory legislation.
Speech recognition technology is racist, study finds
New evidence of voice recognition's racial bias problem has emerged. Speech recognition technologies developed by Amazon, Google, Apple, Microsoft, and IBM make almost twice as many errors when transcribing African American voices as they do with white American voices, according to a new Stanford study. All five systems produced these error rates even when the speakers were of the same gender and age, and saying the exact same words. We can't know for sure if these technologies are used in virtual assistants, such as Siri and Alexa, as none of the companies disclose this information. If they are, the products will be offering a vastly inferior service to a huge chunk of their users -- which can have a major impact on their daily lives.
AI Outlook: Europe initiates AI regulation introducing the principle of trustworthy AI Technology's Legal Edge
On February 19, 2020, the European Commission presented its White Paper on Artificial Intelligence โ A European Approach to Excellence and Trust, a much-anticipated policy document setting out concrete measures and proposed regulation with the objective of promoting the development, uptake and use of AI applications, while also addressing the resulting fundamental rights challenges. The document has raised concerns among companies about whether new rules on AI will negatively impact businesses developing or deploying AI solutions across the EU. Feedback on the white paper can be provided until May 19, 2020. The white paper proposes a dual approach. It aims to establish an "ecosystem of excellence" on the one hand, and "an ecosystem of trust" on the other hand.
AirRL: A Reinforcement Learning Approach to Urban Air Quality Inference
Zhong, Huiqiang, Yin, Cunxiang, Wu, Xiaohui, Luo, Jinchang, He, JiaWei
Urban air pollution has become a major environmental problem that threatens public health. It has become increasingly important to infer fine-grained urban air quality based on existing monitoring stations. One of the challenges is how to effectively select some relevant stations for air quality inference. In this paper, we propose a novel model based on reinforcement learning for urban air quality inference. The model consists of two modules: a station selector and an air quality regressor. The station selector dynamically selects the most relevant monitoring stations when inferring air quality. The air quality regressor takes in the selected stations and makes air quality inference with deep neural network. We conduct experiments on a real-world air quality dataset and our approach achieves the highest performance compared with several popular solutions, and the experiments show significant effectiveness of proposed model in tackling problems of air quality inference.
CCBE Considerations on the Legal Aspects of Artificial Intelligence
The Council of Bars & Law Societies of Europe has recently published a paper discussing some legal aspects of artificial intelligence. The paper first addresses the relationship between artificial intelligence and human rights (especially the right to a fair trial, the right to freedom of expression, the right to freedom of assembly and association, the right to life in the context of smart weapons and algorithmically operated drones, the right to privacy and data protection). Secondly, use of AI by Courts and its criticalities are addressed, particularly non-delegation of the judge's decision-making power, possibility to verify data input and compliance with GDPR. Finally, liability issues and the impact of AI on legal practice are discussed.
How much is too much?: The ethics of AI and data in the workplace
It seems as though we're finally starting to understand just how much influence Artificial Intelligence (AI) can have on our everyday lives. As a concept, AI has technically existed since the 1950s, but it's only within the last few years that we've seen the technology begin to make its lasting mark - from robust and intuitive enterprise technologies right down to the smart devices now powering our homes. Many of us might not be aware, but whether we're using voice assistants such as Alexa, shopping online or scrolling through Facebook, there are various elements of data-heavy AI and Machine Learning (ML) at play. The fact that AI technology has so seamlessly integrated itself into everyday life is certainly remarkable, but this information also arrives with an ethical conundrum. In the days of GDPR, we must now accept cookies in order to consent collection of our personal data outside of work.
Google, Facebook, Neuralink Sued for Weaponized AI Tech Transfer, Complicity to Genocide in China and Endangering Humanity with Misuse of AI - THE AI ORGANIZATION
This is phase 1 of first lawsuit. We are open for support at a global level. We have a network of thousands around the world and tens of thousands in China, who are witnesses and have been harmed in China from the defendants technology and data transfer.The following are Federal Case Compliant Summary Facts Extracted from the official document filed in San Diego, California. To find out details of financial, personal and corrective behavioral demands, you may access the case in the federal court data base.
Legal Tech's Predictions for Artificial Intelligence in 2020 Legaltech News
Are the robot lawyers here yet? My mental picture of C3PO projecting a hologram of a case file has not yet come true, and I must confess that I'm a bit disappointed. OK, I know that's not what artificial intelligence is all about. In the past decade, we have seen AI's legal applications grow from primarily technology-assisted review in e-discovery to encompass everything from legal research to document automation to transactional law. Even if there aren't robot lawyers, AI has begun to fundamentally change how lawyers across the country practice.