未來社會，人工智能將會如何影響我們的生活？

What will be the future of AI in coming future?

2022-04-25 凌波飛雁 9702 10 0 收藏糾錯&舉報

譯文簡介

人工智能的未來走向如何？是給人類社會帶來更多的收益，解決人類社會日常生活中亟待解決的問題，還是像影片中播放的那樣制造出有自主意識的機器人，從而給人類社會帶來災(zāi)難，都尚未可知，引起熱議。

正文翻譯

AI-driven solutions are changing the dynamic structure of the workplace. With AI, current businesses owners are limiting the need for manual data processing that used to consume days of valuable time. AI is helping businesses create a rapid workplace that will continue to develop through the years. Artificial intelligence will continue to rise as more businesses realize its potential. Without AI, businesses will fall behind their competitors due to their instantaneous processing power at a cost-efficient price. Implementations of machine learning processes using AI solutions will further enhance the processing capabilities of your business. The more information processed with AI, the better its performance becomes. This means that business performance only becomes more efficient and understands your process better.

由人工智能驅(qū)動的解決方案正在影響我們的工作和生活。過去，通過人工處理數(shù)據(jù)耗費了很多寶貴的時間。而今，有了人工智能，現(xiàn)有的企業(yè)所有者減少了對人工處理數(shù)據(jù)的需求，從而節(jié)省了不少時間。這一工具正在幫助企業(yè)創(chuàng)建一個快速工作場景，人工智能將在未來持續(xù)發(fā)展。隨著越來越多的企業(yè)意識到人工智能的潛力，人工智能在未來將持續(xù)發(fā)展。以實現(xiàn)機器學(xué)習(xí)過程的人工智能解決方案將進一步增強企業(yè)的業(yè)務(wù)處理能力，如果沒有人工智能，企業(yè)將會因為在處理即時業(yè)務(wù)時的高成本而落后于競爭對手。人工智能處理的信息越多，性能越好。這意味著企業(yè)的業(yè)務(wù)處理能會變得更加高效，并且能更好的了優(yōu)化工作流程。

評論翻譯

1. B. A. Rehl
, Background in computer science and hardware.
Answered 3 years ago · Author has 2.7K answers and 1.1M answer views
AI will become outdated soon and replaced with AGI. This is why I work on AGI theory and not AI which has made very little progress in 60 years.

近60年來進展甚微的人工智能很快就會過時，并且被AGI取代。這就是為什么我研究AGI理論，而不研究人工智能。

1.1 Boyan Dob
Wouldn't AI still be useful for certain specific tasks? Also, AGI will have to freely agree to work with us, no?

人工智能在某些特定的領(lǐng)域不是仍然有用嗎？并且，AGI必須得自愿與我們合作才行，不是嗎？
注釋：AGI(人工通用智能AGI(Artifical General Intelligence)具有對不確定性因素進行推理，使用策略解決問題，制定決策的能力，能夠自主規(guī)劃和學(xué)習(xí)，使用自然語言進行溝通交流的能力)

2. Sharad Suryavanshi
, Stock market enthusiastic
Futures of AI will be brightest among all the contemporary technologies, I as an individual looking forward some of the most amazing fields where AI can establish & impart tremendous results let's dig deeper –
1.Algorithmic trading- forecasting of stocks based on chart reading with the help of machine learning neural networks ,I m very optimistic particularly about the results.

在當代所有的技術(shù)中，人工智能未來將是最光明的。隨著我們不斷的深入挖掘下去，我期待著人工智能能夠在一些最為令人驚嘆的領(lǐng)域里創(chuàng)造出具有驚人影響力的研究結(jié)果。
1.算法交易— 在機器學(xué)習(xí)神經(jīng)網(wǎng)絡(luò)的幫助下，人工智能通過讀取模型圖來預(yù)測股票，我對其預(yù)測結(jié)果的準確性持有樂觀態(tài)度。

2.Debugging- if they can do stock sextion then why not debugging one of the wonderful experience would be to see AI in this field.
It demands very high intense hard work in AI.many years to come for this to come in surface.
3 unmanned work- I will eleborat this with respect to india.there are number of people die in railway unmanned crossing every year . AI robots can play crucial role in such situation.
Moreover they can also diffuse bombs if proper training will be provided to them.

2.選股——如果人工智能能炒股，那為什么不試試呢？在這個領(lǐng)域，人工智能的應(yīng)用將是一個非常美妙的體驗？

在人工智能方面，還需要多年的研究，才能使得人工智能得以發(fā)揮它的作用。
3遙控作業(yè)———我將舉一個例子，在印度，每年都有很多人在鐵路上被撞死，而人工智能機器人在這方面可以發(fā)揮出重大的作用，進而避免很多人發(fā)生鐵路交通事故。此外，如果通過訓(xùn)練人工智能算法，它們還可以拆除炸彈。

4.Self driving cars- This is much talked about topics.Google has done some pioneer & advanced level work too in this field.
A major breakthrough in This field can save millions of life caused by car accident.u can do ur undone work sitting behind
5 Responses based on situation- we have seen preset automated response..but in AI it will uate the condition & deliver the best possible answer according to the situation.

4. 自動駕駛汽車— 一個經(jīng)常被人們談起的話題，谷歌在這方面也做了一些開創(chuàng)性的工作。
原創(chuàng)翻譯：龍騰網(wǎng) http://www.top-shui.cn 轉(zhuǎn)載請注明出處

自動駕駛汽車的重大突破，一方面可以挽救由于車禍而造成的數(shù)百萬人，另一方面也方便人民坐在車后面辦公，完成沒有完成的工作。
5 基于情景反應(yīng)——前提是我們已經(jīng)知道了基于某種情景下預(yù)設(shè)的自動響應(yīng)。而人工智能會根據(jù)情景設(shè)置評估條件，從而提供最佳情景反應(yīng)。

2.1 Joseph
Do you even think how most humans would “benefit” from the total replacement of their jobs? It will be a complete human disaster, where just an elite will (maybe?) benefit from. I cannot see the ones who put their claws on the technology to share the benefits with the rest of the population.

你有沒有想過？人工智能會取代大多數(shù)人的工作，這些人又如何從人工智能中獲益呢？人工智能的發(fā)展，將會是人類的一場災(zāi)難，也許只有精英會從人工智能中獲益，我看不到這些精英會與大多數(shù)人分享人工智能給這個社會帶來的利益。

2.1.1 Sharad Suryavanshi
This question poped up in my feed that's why I answered this..Otherwise I am also against the implications of AI in the area you mentioned.

這個問題出現(xiàn)在我的評論里，所以我來回答一下。但是，我不認同你所提到的也許只有精英會從人工智能中受益，而非大多數(shù)人。

2.1.1.1 Joseph
Hard to control it, once it takes a “l(fā)ife” of its own. We should regulate it and distribute the benefits of it to the whole population. Just saying……

一旦人工智能有了自己的“生命”，就很難控制住它，我們應(yīng)該約束人工智能，并將人工智能所帶來的利益分配給所有人。

3. Clark Hay
, BA and MA from Oral Roberts University (1975)
Like The Internet of Everything (IoE), Artificial Intelligence has already entered almost every aspect of modern life. It is ubiquitous. Barring some catastrophe, it will simply become more and more a part of our lives as time goes on. Already there are predictive algorithms for our preferences in buying, our most likely daily activities, what kinds of people we will be more likely to associate with, what things we will likely want need view or read. Do you use Alexa or Siri? If so then you are using AI. Google’s AI algorithms attempt to match users interests with results and the kinds of advertisements that pop up. Self-driving cars are already a (flawed) reality, and so are computer driven surgeries.

就像物聯(lián)網(wǎng)（IoE）一樣，人工智能已經(jīng)進入了現(xiàn)代生活的每個角落，幾乎是無處不在的。隨著時間的推移，除非發(fā)生一些災(zāi)難，否則人工智能只會越來越多地成為我們生活的一部分。人工智能已經(jīng)有了預(yù)測算法，甚至已經(jīng)掌握了我們的購買偏好、我們?nèi)粘Ｉ钪凶羁赡艿幕顒榆壽E、我們更愿意與什么樣的人交往以及我們最可能需要查看或閱讀的內(nèi)容。谷歌的智能算法推薦系統(tǒng)，試圖將用戶的興趣與用戶的搜索結(jié)果和彈出的廣告類型相匹配，這就是說明。如果你在使用Alexa或者Siri, 那么你已經(jīng)在使用人工智能了。自動駕駛雖然有缺陷，也已經(jīng)成為現(xiàn)實，這也是計算機驅(qū)動的改進，這些都是人工智能的體現(xiàn)。
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Facial recognition, voice recognition, natural language processing, and closed circuit cameras are almost everywhere these days. Algorithms for predicting criminal behaviors are being refined as well for policing purposes, which reminds me of the “Minority Report”. Big Brother already IS a reality. The NSA is absolutely so swamped with data on all of us that its AI algorithms simply can’t sort through all it fast enough to make much of a real difference in deterring crime. Nevertheless profiles are being built at blinding speeds every second of every day and there is no end in sight. And military forces around the globe are using AI every day as well, and virtually every major corporation is utilizing AI in one form or another.

如今，面部識別、語音識別、自然語言處理和閉路攝像頭幾乎無處不在。為了維持治安，預(yù)測犯罪行為的算法也在不斷改進，這讓我想起了影片《少數(shù)派報告》，其中的景象已經(jīng)成為了現(xiàn)實?，F(xiàn)在生活中每時每刻都在以驚人的速度產(chǎn)生著大量的數(shù)據(jù)，并且看不到數(shù)據(jù)的盡頭，國安局的人工智能算法，壓根無法以足夠快的速度對所有的數(shù)據(jù)進行排序，這使得人工智能算法無法在遏制犯罪方面發(fā)揮出真正的作用。世界各地的軍事力量也在每天使用人工智能，幾乎每個大公司都在以這樣或那樣的形式使用人工智能。

A number of companies are beginning to develop AI programs to analyze our emotions motivations moods, and psychological make up. Some are trying to understand or mimic those aspects of the human mind that shape our wants and needs and preferences and motivations and creativity - pointing the way to some future sentient autonomous self-aware and perhaps even conscious computer based entity .

許多公司開始研發(fā)人工智能程序，借助于這些程序分析人類的產(chǎn)生某種活動的情緒、動機和心理構(gòu)成。有些人甚至試圖讓人工智能程序去理解或人類的思維方式，這些思維創(chuàng)造了我們的欲望，需求，偏好，動機和創(chuàng)造力。這些人工智能程序為未來研發(fā)一些有知覺的、自主的、甚至是有自我意識的機器人指明了方向和道路。

In my own mind I find this last prospect frightening. Such a sentient autonomous self-aware and conscious computer that could teach itself would most likely pass through a “juvenile” stage where it believes it is smarter than its creators - or at least bolder. And once it “matures” it will likely perceive itself to be our superior.

如此一個有知覺、自主、擁有自我意識、能夠自我教育的機器人可能會經(jīng)歷一個“幼稚”階段，在這個“幼稚”階段，這個機器人會認為自己比創(chuàng)造它的人更聰明，或者甚至更大膽。一旦這個機器人“成熟”，它可能會認為自己是我們的領(lǐng)導(dǎo)者。我認為，讓機器擁有自我意識的這個前景是很可怕的。

Would such a machine be able to hack into every other system to control things? Would it create a host of other sentient programs to do its bidding? Would it decide to oppose us as so many movies suggest? … As silly as that may sound to some, the prospect is quite frightening to others. And once the “genie” (jinn) is out of the bottle, could it be put back in or controlled, or will it deceptively hide it’s abilities until it is too late?

這樣一個擁有自我意識的機器人，有沒有可能侵入其他所有的系統(tǒng)來控制人類生產(chǎn)出來的機器？有沒有可能會創(chuàng)造出很多其他擁有感知能力的機器來執(zhí)行它的命令？甚至?xí)裨S多其他電影中播放出來的那樣，反對人類呢？這聽起來似乎很愚蠢，但對有些人來說確實是的，可對其他人來說確是相當可怕的?？梢韵胂螅坏熬`”從瓶子中出來，那么它會被放回去嗎？或者會被控制嗎？又或者會一直選擇欺騙性地隱藏自己的能力？

Elon Musk has all but given up warning world leaders of possible future problems with AI, but believes that directly connecting human brains to interface with the Internet might be a good thing. If you can’t beat AI, join with it. But becoming part of the collective Borg does not sound like the kind of a future I want to be a part of. As I have already noted elsewhere, we are already drowning in information. Having more information is NOT the answer. Having more money is NOT the answer. Having extended lives is NOT the answer. Without curiosity, the will to work hard, and the desire to do our own thinking to process and uate all of that information using well honed critical thinking skills with enhanced wisdom and compassion, none of the rest matters.
Unplug, turn off, drop out.

關(guān)于人工智能未來可能出現(xiàn)的問題，埃隆·馬斯克幾乎已經(jīng)不再警告世界各國了，但是他認為，如果你不能打敗人工智能，那么就加入它，將人類的大腦和互聯(lián)網(wǎng)直接連接起來，也許是件好事。但這樣的未來并不是我想要的未來。正如我在之前提到的那樣，而今我們已經(jīng)淹沒在信息當中，可是，擁有更多的信息、金錢，壽命的延長，不是最終的目的。如果人工智能時代使得未來社會缺少了好奇心、努力工作的意愿，甚至沒有了自主思考解決和評估問題的意愿、沒有了經(jīng)過磨練的批判性思維技能、沒有智慧和同情心，那么人工智能能夠給我們帶來就只剩下拔掉插頭、關(guān)閉和退出，這一切又有什么意義呢。

3.1 Torben M?lgaard
Regarding the AI emotions thing, I read a few years ago that Japanese authorities are actually utilizing software which in real time can assert threatening or agitated voice patterns and alx someone to take a closer look. Subways and such. Creepy stuff. And as you say, it’s crawling in, more and more places.

我?guī)啄昵白x到過有關(guān)人工智能情感案例，在日本，實際上正在使用一款軟件，該軟件可以通過實時監(jiān)控威脅或激動的聲音模式，實現(xiàn)提醒某人留心附近危險的事情。正如你所說的，令人毛骨悚然的人工智能已經(jīng)爬進了越來越多的地方。

3.1.1 Clark Hay
Agreed

我認同

3.2 Joseph
Yes, not many see it, though…

是的，雖然看的不多……

3.3 Roni Patterson
In that we humans have no idea what consciousness is, nor where it comes from nor where it’s located, how can anybody expect a machine to figure that out? Plus, machines aren’t even organic. Consciousness is now referred to as the “Hard Problem” among the science community.

在科學(xué)界里意識被稱為“難題”，既然我們?nèi)祟惗疾恢?。什么是意識，也不知道意識是從哪里來，又存在哪里？那么又如何指望的上機器人能夠找出這個答案呢？再說了，機器甚至都不是有機生物，哪來的意識？

4. Ben Taylor
, studied Artificial Intelligence & Startups at The Internet
AI will continue to surprise us, delight us, and scare us.

Job Reduction
Jobs that were never considered to be replaceable will see full replacement with automation. Everyone talks about professional drivers with self driving cars, but I think in the next 10 years you will see pull back on many other positions. Positions like talent assessment, appraisers, dermatologists, radiologists, pathologists, lawyers, court transcxtionists, cashiers, security personnel, psychologists, manufacturing QA technicians, and professors. Anything where a human is listening, or visually reviewing repetitive tasks. Job loss estimates will climb from the commonly referenced 7% to something closer to 15%.

人工智能持續(xù)給我們?nèi)祟悗眢@喜，讓我們高興的同時也讓我們害怕。
工作機會減少
每個人都在談?wù)撟詣玉{駛汽車的職業(yè)司機，那些曾經(jīng)無可替代的工作將被自動化完全取代。但我認為，在未來十年里，將會有更多的職位減少，這些職位包括人才評估、評估師、皮膚科醫(yī)生、放射科醫(yī)生、病理學(xué)家、律師、法庭轉(zhuǎn)錄員、收銀員、保安人員、心理學(xué)家、制造QA技術(shù)人員和教授。估計在聽或視覺上任何有人類重復(fù)工作的地方，失業(yè)將從通常所指的7%攀升至接近15%的水平。

Delight Us

使我們感到興奮
原創(chuàng)翻譯：龍騰網(wǎng) http://www.top-shui.cn 轉(zhuǎn)載請注明出處

Safety and medical will see new records on lives lost reduced and detection accuracy increases. Did you know that in the US we average 2 kids in ERs per day and 1 dead child per month for window blind cord strangulation? Terrible metrics like this will see 1–2 order of magnitude decrease with AI. In the future every home will have 100s or even 1000s of micro cameras powered by AI. The moment anything happens in your home worthy of your review (i.e your toddler is being strangled by a blind cord) your home will contact your mobile device and escalate to neighbors if needed. On the medical side we will continue to hit high marks on detection and diagnosis. Lone wolf terrorism impact and time to intervene will continue to improve. In the future our ability to respond to something like a school shooting will allow for sub-minute control (i.e. autonomous drones with non-lethal mace/taser response ). Unnecessary deaths with deadly police force (i.e. youth in hoodie being mistakenly shot at night for holding a toy gun) will be reduced 1–2 orders of magnitude thanks to autonomous super-human threat assessments via micro-drones. Police deaths will also decrease 1–2 orders of magnitude by reducing their exposure and time-to-respond.

你知道嗎？在美國。平均每天有兩個孩子被送進急診室，每個月有一個孩子死于窗簾線勒死，像這樣糟糕的數(shù)字將會隨著AI人工智能的發(fā)展而減少1-2個數(shù)量級，這在一定程度上減少了安全隱患，提高了醫(yī)療檢測的準確性，進而減少了生命的損失。在未來，每個家庭都將擁有100個甚至1000個由人工智能驅(qū)動的微型攝像頭，一旦家里發(fā)生任何危險的事情。（比如你的孩子被窗簾線勒住了），你的AI就會聯(lián)系你的移動設(shè)備。并在需要的時候聯(lián)系鄰居。減少危險事情的發(fā)生。在醫(yī)療檢測和診斷方面，人工智能將繼續(xù)取得高分。獨狼恐怖主義的影響和干預(yù)時間將持續(xù)得到改善。未來，人工智能在應(yīng)對校園槍擊案等事件方面，將會實現(xiàn)快速控制（例如具有非致命性的自主無人機）。利用微型無人機進行的超級人類自動威脅評估，警察的致命武力造成的不必要死亡（例如穿帽衫的年輕人晚上拿著玩具槍被誤殺）數(shù)量將減少1-2個數(shù)量級，人工智能的使用減少了警察暴露和反應(yīng)時間進而使得警察的死亡數(shù)量減少1-2個數(shù)量級。

4.1 Gayatri Puwar
Love delight us scenarios, to strive for. Thanks for the balancing act. Job reduction aspect not so drastic as it's nothing new, happens every decade. Scare us - now that is something we need to be careful for, all who practice it to develop with ethics and big MNCs are therefore developing principles around these, as always technology in wrong hands is devastating, not just limited to AI, think burner phones in hand of terrorists, and how mobile industry (at most, not solved completely) required Global SIM and IMSI registrations for example.

愛使我們快樂，為之努力奮斗吧。感謝你的闡述。裁員方面并沒有那么激烈，只是在嚇唬我們，因為這不是什么新鮮事，每十年都會發(fā)生一次。想想恐怖分子手中的一次性手機，以及移動產(chǎn)業(yè)（最多，沒有完全解決）如何要求全球SIM和IMSI注冊的事情，現(xiàn)在我們需要小心的是所有圍繞道德與實踐而發(fā)展大型跨國公司借助人工智能為所欲為，而不僅僅是限制人工智能，因為技術(shù)落入壞人手中是毀滅性的。
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5. Yisong Yue
Machine Learning Professor @Caltech
Answered May 31, 2017 · Upvoted by Haris Muneer, BS Computer Science, National University of Computer and Emerging Sciences (2019)
To me, the most pressing challenge of AI in the foreseeable future is combining it with concepts from other engineering fields. As AI becomes more integrated into our daily lives, addressing issues like safety and fairness will become central to how we think about developing and deploying AI systems.
Safety Critical AI. Machine learning generally does not come with any guarantees beyond (usually fairly loose) generalization bounds. Certifying rare events is very challenging. For instance, suppose an aerospace company wants to use data-driven methods to design better aircrafts (btw, this is basically EVERY aerospace company). How can we certify that the aircraft won’t crash out of the sky with 99.99999% probability? Currently, the controller on an aircraft has extremely deterministic behavior. But as you design more flexible controllers using machine learning, you necessarily allow for non-determinism to creep into the process (or at least you can’t exhaustively quantify all the behavior in the same way as before). Similar issues arise with self-driving cars, personal robots that walk your dog, etc. In general, as we integrate AI with cyberphysical systems, guaranteeing safety becomes extremely important.

我認為，在可預(yù)見的未來，隨著人工智能越來越融入我們的日常生活，人工智能最緊迫的挑戰(zhàn)是如何將其與其他工程領(lǐng)域的概念相結(jié)合，解決安全和公平等問題將成為我們?nèi)绾伍_發(fā)和部署人工智能系統(tǒng)的核心。因為，證明罕見事件是非常具有挑戰(zhàn)性的，通常不會認為機器學(xué)習(xí)會超出相當寬松的泛化界限的保證。例如，假設(shè)一家航空公司想要使用數(shù)據(jù)驅(qū)動的方法來設(shè)計更好的飛機(順便說一下，這基本上是每家航空公司的目標)。目前，飛機上的控制器具有非常確定性的行為，但當你使用機器學(xué)習(xí)設(shè)計更靈活的控制器時，你必須允許非決定論滲入這個過程(或者至少你不能像以前那樣徹底量化所有的行為)，我們?nèi)绾我?9.99999%的概率保證飛機不會墜毀?類似的問題也出現(xiàn)在自動駕駛汽車、幫你遛狗的個人機器人等領(lǐng)域。總的來說，當我們將人工智能與網(wǎng)絡(luò)物理系統(tǒng)整合在一起時，保證安全變得極其重要。

Fairness in AI. Machine learning systems learn from the data that is given to them. If the data itself is biased, then the resulting system will be as well. For instance, many industries are using data-driven algorithms to make decisions such as lending, predictive policing, sentencing for crimes, just to name a few. A key issue in these settings is maintaining fairness. Just like how humans can be biased by the information they consume, so can machines. For example, if certain neighborhoods had a high volume of crime incidences recorded, then predictive policing would send more police patrols into that neighborhood, potentially leading to an even higher amount of crime incidences recorded, which is then fed back into the predictive policing system. See also: algorithmic fairness.

人工智能是公平的。機器學(xué)習(xí)系統(tǒng)從提供給它們的數(shù)據(jù)中學(xué)習(xí)。如果數(shù)據(jù)本身有偏差，那么結(jié)果系統(tǒng)也會有偏差。許多行業(yè)正在使用數(shù)據(jù)驅(qū)動的算法輔助決策，例如，利用算法輔助做出貸款、預(yù)測警務(wù)、對犯罪進行判決等決策，這只是其中的幾個例子。在這些算法設(shè)置中，一個關(guān)鍵問題是如何保持公平？就像人類會從日常生活的事件中而產(chǎn)生偏見一樣，機器也會。例如，如果某些社區(qū)記錄了大量的犯罪事件，那么預(yù)測性警務(wù)就會向該社區(qū)派遣更多的警察巡邏，這可能會導(dǎo)致記錄的犯罪事件數(shù)量更高，然后反饋到預(yù)測性警務(wù)系統(tǒng)，這就缺失了公平。參見:算法公平。

5.1 Joseph
Like we don’t have enough competition for good jobs. AI will eliminate most of them, so all humanity will live on subsistence levels and the elite will enslave us. That unless AI will eliminate humans altogether anyway.

除非人工智能將來徹底消滅人類，否則人工智能將取代大部分人的工作，所以全人類將生活在勉強糊口的水平上，精英將奴役我們。就像我們?nèi)狈Ω偁巸?yōu)勢無法獲得好工作一樣。
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5.2 Randy Goebel
Both Yogi Berra and Neils Bohr noted their reluctance to make predictions, especially about the future ;-) Issues of reliability and “fairness” have always been an issue in complex systems, and AI doesn’t change that. I put “fairness” in quotes because it is a complex term itself … an individual or organization’s view of fairness varies widely. But the truth is that EVERY small advance in every science (including AI, ML, nano science, systems biology) entails the need for reconsideration of engineering methods, so Yisong Yue is correct … but correct generically … whether engineers are able to adapt and exploit scientific advances is always a question, and will always be, regardless of whether the advances are in AI or elsewhere.

尤吉·貝拉和尼爾斯·玻爾都表示，他們不愿做出預(yù)測，尤其是對未來的預(yù)測;-)可靠性和“公平性”問題一直是復(fù)雜系統(tǒng)中的一個問題，而人工智能不會改變這一點。我之所以將“公平性”打上引號，是因為個人或組織對公平的看法各不相同，公平本身就是一個復(fù)雜的術(shù)語。但事實是,在每一個科學(xué)(包括人工智能、ML、納米科學(xué)、系統(tǒng)生物學(xué))中每一個小小的進步，都需要對工程方法進行復(fù)議,所以，岳義松總的來說是正確的……然而，工程師是否能夠適應(yīng)和利用科學(xué)進步始終是一個問題, 不管這些進步是在人工智能領(lǐng)域還是在其他領(lǐng)域，工程師是否能夠適應(yīng)和利用科學(xué)進步永遠都是一個問題。

未來社會 人工智能 生活

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未來社會，人工智能將會如何影響我們的生活？