人工智能的未来
AI is entering its third wave, where machines can assess context of data to make their own decisions. 这会产生什么新能力，是否有陷阱? 在零压力播客中, our host Helen Sharman is joined by experts Tero Ojanperä 还有凯伦·黑格博士 to discuss the implications of AI’s third wave.
教育, greater transparency and trust are the keys to widesp读 acceptance of artificial intelligence (AI)’s third wave, according to our two AI experts in the third episode of Imperial College London and Saab’s 零压力播客.
都是Tero Ojanperä, Silo的联合创始人, 北欧地区最大的私人人工智能实验室, 还有凯伦·黑格博士, 物理系统的认知技术专家, 你相信更先进的人工智能能力能带来的好处吗.
Yet they also tell podcast host Helen Sharman that they are equally certain that we must be clear about how and why the technology operates as it does, 既不否认，也不不假思索地接受, 我们必须掌控局面.
“We as humans have to be able to put the appropriate boundaries on it,黑格博士说.
“这和你在家里对蹒跚学步的孩子所做的没什么不同. You set up fences around that child to make sure that it is learning the things you want it to learn.”
先进的能力，巨大的潜力
人工智能自上世纪50年代就出现了, when it began with simple statistical processes before expanding into machine learning in the 1960s. 然而，在过去的十年里，它一直在以惊人的速度发展.
The third wave of AI promises machines that can contextualise data points. “这是我们人类一直在做的事情, 例如，在理解路标的意思时, 即使它被泥土覆盖，几乎看不见,海伦·沙曼说. We are al读y seeing this type of AI make its way into self and assisted-driving cars, for example.
Tero Ojanperä 还有凯伦·黑格博士 both believe that this new wave of AI has great potential in a number of applications, 包括学校教育, 供应链管理和协调对自然灾害的反应.
“It’s not about AI taking over but about AI supporting people in their daily work, helping to solve big problems and in this way making the world a better place. 这是关于重新思考我们如何看待人工智能，”Ojanperä说.
“When we think about the teaching process, AI can collect data on learning in a digital environment. 你可以更好地看到谁落后了，给他们个别的支持. 在教学方面，人工智能可以进行互动. 它可以在很多场合做老师, like a chatbot that many of us have communicated with in customer service applications.”
实现人工智能承诺的关键
这与现在的一项技术相吻合，该技术使机器能够将数据置于环境中, our experts think that seeing AI in context is key to its integration and acceptance into our lives. 他们都不认为这是对人类的威胁.
黑的博士, 谁写过人工智能在电子战中的作用, sees the technology as being well suited to rapid handling of complex tasks in restricted situations, 比如战场.
“如果我们关注一个关键的国防部门, 具有硬实时操作约束的情况, 事情必须在很短的时间内完成. 你使用的是小型嵌入式设备. 你不能回到云端去做大量的计算. 我们需要迅速做出正确的决定，”她解释说.
“The other major difference in military situation is that there are often no previous learning examples. 这是实时的, in-mission learning and there are systems that will go out with no data at all. Mars Rover has no time to go back to Earth regarding every decision that it’s making. 人工智能只是一个工具, 就像一套可以用来解决问题的数学工具, 它在偏远和崎岖的环境中特别有用.”
And Tero Ojanperä adds: “There are so many benefits but it’s very important that we are transparent about AI, not only in education but if people are communicating with a chatbot in a customer service situation - if you think it’s a human and then find out that it’s AI you might become angry or disappointed. It’s all about being transparent and explaining in simple terms how it works.”
对于两位专家来说，知情信任至关重要.
“If we consider motor cars with lane following and cruise control – we have been accepting them, 所以它是从最低层次开始建立对人工智能的信任,黑格博士说.
“人工智能仍然像人类一样. 它有时会出错，”Ojanperä补充道. “If I understand that it can have control of the car yet I still need to be alert, that works. So long as we don’t trust blindly, and have transparency, the world is our oyster.”
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