【英文】2022年新兴科技趋势报告（161页）

英文研究报告 2022年05月03日 06:55 管理员

Advanced machine learning is only possible with signifcant amounts of data—ofen user data that includes personally identifable information. Both the collection and the use of this data raise compliance and ethical risks that companies may need to address. One of the main risks is the use of data for purposes that were not anticipated at the time the data was collected. This may occur when companies purchase or leverage thirdparty datasets to train their algorithms. From a commercial perspective, the key is to provide appropriate notice, and secure appropriate consent, when collecting the personal information—or ensure that a supplier has done the same, even though the AI supply chain is increasingly complex.As AI technology becomes more deeply embedded in a wide variety of tools to support decision-making, reports have emerged alleging that the algorithms, data, and models used in these systems may demonstrate biases.

There has been an increase in lawsuits against companies and organizations that use “black box” AI tools to provide guidance for decisions related to areas such as employment, consumer credit, or criminal justice.Other developments indicate views might be shifing in those jurisdictions, however. For example, in 2021, the U.K. Intellectual Property Ofce (UKIPO) released a report on consultations it had conducted regarding the impact of AI on intellectual property. Included in the report was the suggestion that UKIPO could eventually seek legislation allowing AI tools to be recognized as inventors. According to a UKIPO ofcial, “We recognise that AI systems have an increasing impact on the innovation process. We want to ensure the intellectual property systems support and incentivise AI-generated innovation.”