【正确答案】 A

【答案解析】[听力原文]
   Here is my baby niece Sarah. Her morn is a doctor and her dad is a lawyer. By the time Sarah goes to college, the jobs her parents do are going to look dramatically different.
   In 2013, researchers at Oxford University did a study on the future of work. They concluded that almost one in every two jobs has a high risk of being automated by machines. Machine learning is the technology that's responsible for most of this disruption. It's the most powerful branch of artificial intelligence. It allows machines to learn from data and copy some of the things that humans can do. My company, Kaggle, operates on the cutting edge of machine learning We bring together hundreds of thousands of experts to solve important problems for industry and academia. This gives us a unique perspective on what machines can do, what they can't do and what jobs they might automate or threaten.
   Machine learning started making its way into industry in the early '90s. It started with relatively simple tasks. It started with things like assessing credit risk front loan applications, sorting the mail by reading handwritten zip codes. Over the past few years, we have made dramatic breakthroughs. Machine learning is now capable of far, far more complex tasks. In 2012, Kaggle challenged its community to build a program that could grade high-school essays. The winning programs were able to match the grades given by human teachers.
   Now, given the tight data, machines are going to outperform humans at tasks like this. A teacher might read 10,000 essays over a 40-year career. A machine can read millions of essays within minutes. We have no chance of competing against machines on frequent, high-volume tasks.
   But there are things we can do that machines cannot. Where machines have made very little progress is in tackling novel situations. Machines can't handle things they haven't seen many times before. The fundamental limitation of machine learning is that it needs to learn from large volumes of past data. But humans don't. We have the ability to connect seemingly different threads to solve problems we've never seen before.
   What did the researchers' at Oxford University conclude?
录音开头说牛津大学的研究人员对未来的工作进行了研究，他们得出的结论是，几乎每两个工作岗位中就有一个具有被机器实现自动化的高风险(almost one in every two jobs has a high risk of being automated)。A项“目前大约一半的工作可能是自动化的”与此相符，为答案。
   B项利用录音中的doctor和lawyer作干扰，录音是说萨拉的妈妈是医生，爸爸是律师。到她上大学时，父母做的工怍看起来会截然不同，并非B项说的“医生和律师的工作将受到威胁”。录音未提及就业市场正变得有些不可预测，也没说到2013年，机器学习将证明具有破坏性。故排除C、D两项。