On February 19, 2020, the European Union Commission issued a plan for regulating high-risk artificial intelligence (AI) technologies developed or deployed in the EU. Calling it a “White Paper on Artificial Intelligence: a European Approach to Excellence and Trust,” the plan was published along with a companion “European Strategy for Data” and follows an earlier
On February 19, 2020, the European Union Commission issued a plan for regulating high-risk artificial intelligence (AI) technologies developed or deployed in the EU. Calling it a “White Paper on Artificial Intelligence: a European Approach to Excellence and Trust,” the plan was published along with a companion “European Strategy for Data” and follows an earlier
When Microsoft shared in 2018 that certain “deficiencies” surrounding its artificial intelligence practices could “subject[] us to competitive harm, legal liability, and brand or reputational harm,” it set the stage for other companies to self-report perceived risks associated with developing, using and producing AI technologies. Disclosing risks–a Securities and Exchange Commission (SEC) requirement imposed on
When Microsoft shared in 2018 that certain “deficiencies” surrounding its artificial intelligence practices could “subject[] us to competitive harm, legal liability, and brand or reputational harm,” it set the stage for other companies to self-report perceived risks associated with developing, using and producing AI technologies. Disclosing risks–a Securities and Exchange Commission (SEC) requirement imposed on
When Microsoft shared in 2018 that certain “deficiencies” surrounding its artificial intelligence practices could “subject[] us to competitive harm, legal liability, and brand or reputational harm,” it set the stage for other companies to self-report perceived risks associated with developing, using and producing AI technologies. Disclosing risks–a Securities and Exchange Commission (SEC) requirement imposed on
Imagine you’ve spent months developing and deploying a revenue-generating deep neural network model only to discover that an attacker has stolen the model’s knowledge and will soon offer a service that will steer potential users away from yours. Flashes of late nights and weekends spent collecting and cleaning data cross your mind, accompanied by a
Imagine you’ve spent months developing and deploying a revenue-generating deep neural network model only to discover that an attacker has stolen the model’s knowledge and will soon offer a service that will steer potential users away from yours. Flashes of late nights and weekends spent collecting and cleaning data cross your mind, accompanied by a
Imagine you’ve spent months developing and deploying a revenue-generating deep neural network model only to discover that an attacker has stolen the model’s knowledge and will soon offer a service that will steer potential users away from yours. Flashes of late nights and weekends spent collecting and cleaning data cross your mind, accompanied by a
Machine learning enthusiasts have long touted the technology’s ability to perform–and sometimes exceed–human mental endeavors, such as identifying objects in images, generating a portrait painting, deciding to grant a loan application, optimizing a route to a destination, and efficiently responding to website visitor or customer queries. In recent years, such computerized “mental processes” have been
Machine learning enthusiasts have long touted the technology’s ability to perform–and sometimes exceed–human mental endeavors, such as identifying objects in images, generating a portrait painting, deciding to grant a loan application, optimizing a route to a destination, and efficiently responding to website visitor or customer queries. In recent years, such computerized “mental processes” have been
Machine learning enthusiasts have long touted the technology’s ability to perform–and sometimes exceed–human mental endeavors, such as identifying objects in images, generating a portrait painting, deciding to grant a loan application, optimizing a route to a destination, and efficiently responding to website visitor or customer queries. In recent years, such computerized “mental processes” have been
In Patel v. Facebook, a three-judge panel of the U.S. Court of Appeals for the 9th Circuit affirmed a decision by the U.S. District Court for the Northern District of California granting class certification to users of Facebook who alleged that Facebook’s collecting and storing of their face scans using facial recognition technology violated
In Patel v. Facebook, a three-judge panel of the U.S. Court of Appeals for the 9th Circuit affirmed a decision by the U.S. District Court for the Northern District of California granting class certification to users of Facebook who alleged that Facebook’s collecting and storing of their face scans using facial recognition technology violated
In Patel v. Facebook, a three-judge panel of the U.S. Court of Appeals for the 9th Circuit affirmed a decision by the U.S. District Court for the Northern District of California granting class certification to users of Facebook who alleged that Facebook’s collecting and storing of their face scans using facial recognition technology violated
Developers of artificial intelligence-based video interviewing systems promote their technology as one that helps human resource professionals on-board new talent faster, less expensively, and with greater insight compared to traditional human-only interviewing techniques. They also contend that their systems can avoid some of the potential implicit biases that may appear before, during, and after interviews,
Developers of artificial intelligence-based video interviewing systems promote their technology as one that helps human resource professionals on-board new talent faster, less expensively, and with greater insight compared to traditional human-only interviewing techniques. They also contend that their systems can avoid some of the potential implicit biases that may appear before, during, and after interviews,