金融時報:無人駕駛超越人類？

所屬教程:金融時報原文閱讀

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2021年09月28日

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無人駕駛超越人類？

一位先鋒工程師表示：當(dāng)人類司機出現(xiàn)失誤，他會自己從中學(xué)習(xí)到經(jīng)驗；而一輛無人駕駛的汽車出現(xiàn)失誤時，其他每一輛“汽車伙伴”都將從中吸取教訓(xùn)并且避免“無人駕駛司機”必然會超過人類司機——只是時間早晚的問題。

測試中可能遇到的詞匯和知識：

banal陳腐的；平庸的；老一套的[b?'nɑ?l; -'n?l]

outlandish古怪的；奇異的[a?t'l?nd??]

commonplace老生常談；司空見慣的事；普通的東西['k?m?nple?s]

flurry疾風(fēng)；颶風(fēng)；騷動['fl?r?]

sit idle坐視不管

clog up堵塞

smash into猛撞在……

boon恩惠；福利；利益

congestion擁擠；擁塞

envisage正視，面對；想像[?n'v?z?d?; en-]

whizzing發(fā)出嗖嗖聲；嗖嗖掠過['wizi?]

astonishing驚人的；令人驚訝的[?'st?n????]

throng人群；眾多[θr??]

inevitably不可避免地；必然地[?'nev?t?bl?; ?n'ev?t?bl?]

backlash反沖；強烈抵制['b?kl??]

provoke驅(qū)使；激怒；煽動；惹起[pr?'v??k]

visionary空想家；夢想者；有眼力的人['v??(?)n(?)r?]

dichotomy paradox兩分法悖論：在兩分法悖論中，芝諾要論證的是：一個正在行走的人永遠(yuǎn)到達不了他的目的地，因此，運動是不可能的。

Stalinist斯大林主義：是指控制蘇聯(lián)和受蘇聯(lián)影響的社會主義陣營內(nèi)的國家，在約瑟夫·斯大林統(tǒng)治下及其之后的共產(chǎn)主義理論。

Humans are the main obstacle to the driverless revolution （737 words）

By John Thornhill

Brilliant technologies transform the magical into the banal. An idea that seems outlandish to one generation becomes commonplace to the next. So it has been with electricity, space flight and the internet. So it is likely to prove with driverless cars.

The past few weeks have seen a flurry of announcements. Singapore has launched the world's first public trial of a robo-taxi service. Uber and Volvo announced that they would pioneer an autonomous taxi fleet in Pittsburgh within weeks. Ford said it would build its first mass-market driverless car by 2021.

To their backers, autonomous cars cannot arrive quickly enough. Conventional cars are inefficient, dangerous and dirty. They sit idle for 95 per cent of their lives, clogging up city streets and car parks. When moving, they smash into each other, killing 3,500 people every day around the world. Ninety per cent of accidents are caused by human error. Cars pollute the environment, accounting for 45 per cent of oil burnt.

The widespread adoption of fully autonomous and, still better, electric cars could therefore be a massive boon to mankind. It could lead to a far more efficient use of resources, save many lives and reduce congestion and pollution. Futurologists envisage small fleets of shareable, connected cars constantly whizzing around our cities picking up passengers on demand. McKinsey forecasts that 15 per cent of new cars could be fully autonomous by 2030.

But two obstacles block their widespread adoption. The first remains technological. For all the astonishing advances made in recent years, it is phenomenally difficult to replicate humans as sensory beings.

How does a car distinguish between a plastic bag blowing across a road and a runaway dog? How does a car nudge its way through a throng of people outside a football stadium?

Engineers argue that the genius of self-driving cars is their connectedness. “When human drivers make a mistake the individual learns from it,” says one Silicon Valley pioneer. “When a self-driving car makes a mistake then every other car will learn from a mistake once an engineer has fixed it. It is just a matter of time before our technology surpasses human capacity.”

But sceptics compare autonomous car technology with Zeno's dichotomy paradox: every leap will take us halfway to our destination without ever reaching it.

No matter how hard the technology proves, it may be the easier part of the puzzle. A stiffer challenge remains the human. Even when manufacturers and software engineers develop fully autonomous cars in which they have total trust, it will still take many years, if not decades, for them to be freely embraced by governments and consumers.

First, there is the instinctive human resistance to handing over control to a robot, especially given fears of cyber-hacking. Second, for many drivers cars are an extension of their identity, a mechanical symbol of independence, control and freedom. They will not abandon them lightly.

Third, robots will always be held to far higher safety standards than humans. They will inevitably cause accidents. They will also have to be programmed to make a calculation that could kill their passengers or bystanders to minimise overall loss of life. This will create a fascinating philosophical sub-school of algorithmic morality. “Many of us are afraid that one reckless act will cause an accident that causes a backlash and shuts down the industry for a decade,” says the Silicon Valley engineer. “That would be tragic if you could have saved tens of thousands of lives a year.”

Fourth, the deployment of autonomous vehicles could destroy millions of jobs. Their rapid introduction is certain to provoke resistance. There are 3.5m professional lorry drivers in the US.

Fifth, the insurance industry and legal community have to wrap their heads around some tricky liability issues. In what circumstances is the owner, car manufacturer or software developer responsible for damage?

Some governments, such as those of Singapore, China and the UK, as well as several states in the US are creating permissive regulatory and legal environments. Regulators can certainly speed adoption by approving designated lanes for autonomous cars, for example, and devising international safety rules and standards. Conversely, politicians may yet succumb to the pressure of public fears and vested interests and frustrate the roll out of self-driving cars.

Autonomous car visionaries may soon be able to perfect the technology. But their success may be determined by how good they are — in Stalinist terminology — as engineers of human souls.

請根據(jù)你所讀到的文章內(nèi)容，完成以下自測題目：

1.When will Ford build its first mass-market driverless car?

A.2017

B.2020

C.2021

D.2025

答案(1)

2.Which is not right about the conventional cars?

A.inefficient

B.dangerous

C.fast speed

D.dirty