What's Next in AI: a conversation on AI and the workplace

Summary

录像脚本涉及了IBM如何在人力资源管理中使用AI和自动化。讨论了实验、员工适应性、以及AI伦理原则等相关话题。使用AI带来的好处包括:更快的响应时间、让人类专注于更复杂的工作。

Takeaways

• 😀 人工智能正在重塑企业的人才管理
• 😊 人工智能有助于提高员工满意度
• 😎 实验和迭代非常重要
• 🤓 必须实施人工智能伦理原则
• 🧐 数据和模型健壮性至关重要
• 🤔 人工智能并不总是一个完美的解决方案
• 😌 人工智能释放了人力资源专注更高价值的工作
• 🙂 必须在人工智能中保持透明度
• 🤩 人工智能正在创造新的工作机会
• 😄 不要害怕人工智能,立即开始吧!

Q & A

IBM在人工智能领域有哪些核心原则?

IBM有几个核心原则:1)人工智能是用于增强人类智能的;2)在内部流程中,人工智能永远不是决策者;3)数据和见解属于创建者。

人工智能如何改变IBM的内部运营?

人工智能改变IBM内部运营的三个方面:1)确保每一美元的投资都取得最大回报;2)运营环境变得更加复杂;3)员工期待个性化的消费级体验。

AskHR这一人工智能助手每年处理多少次对话?

AskHR每年处理150万次对话。

人工智能助手改善了IBM的净推荐值吗?

是的,数字化层面的净推荐值提高到+35,在某些流程中甚至达到+70,这意味着员工获得了更好的用户体验。

人工智能如何提升HR从业人员的职业发展?

通过处理更多高价值工作,HR从业人员的平均级别提高了一个完整的级别或档次,为他们带来了更好的职业发展。

人工智能自动化如何提高IBM的升职流程效率?

在一个典型需时一个季度的升职流程中,Watson Orchestrate的自动化工具节省了12,000个工作小时。

人力资源主管应该如何调整方法来应对人工智能创新?

他们可以从两方面入手:1)引入数字助手改善基本查询和交易;2)应用自动化改进人才生命周期中的流程。

实施人工智能需要注意什么原则?

需要注意的几个关键原则:可解释性、透明度、公平性、健壮性。这可以建立用户信任,确保合规。

视频中IBM HR负责人建议企业家从哪几个方面着手使用人工智能?

她建议从这几个方面着手:1)准备实验;2)在试验中平衡风险;3)从小规模开始;4)在实施过程中争取倡导者并从用户那里获得反馈。

人工智能真的会带来失业风险吗?

不会。IBM认为人工智能实际上会成为净创造就业机会的技术。因为它会把人力资源从单调和行政工作中解放出来,转为从事更加创新和创造性的工作。

Outlines

00:00

🤖 人工智能与劳动力转型

这段对话介绍了IBM如何应对人工智能、自动化技术与人力劳动的融合挑战。IBM的首席人力资源官Nicool Lamro强调，公司通过重塑技能培训来适应技术变革，特别是在人工智能领域。IBM有超过250,000名员工参与到人工智能革命中，无论是产品开发、客户服务还是内部职能改进。她强调，技术培训和实践的机会对于员工技能提升至关重要，并且这种转变是渐进式的，而非一蹴而就。此外，讨论还触及了智能自动化、机器辅助人类决策、人类对机器的补充以及在何时加入人类触感等问题。IBM对人工智能的应用遵循明确原则，即增强人类智能而非取代，确保人类始终参与决策过程，保护数据及洞察归创造者所有。

05:01

📈 人工智能对工作场所的积极影响

在这一段中，讨论集中在人工智能如何成为创造就业机会而非取代人类工作的力量。IBM认为，通过自动化处理重复性、行政性质的任务，人工智能使人们有更多时间进行创新和创造性工作，从而为企业创造更大的价值。这不仅为企业带来好处，同时也为处于人口减少或劳动力短缺国家的人们创造了新的机遇。文章还强调了企业需要采取的措施来充分利用人工智能带来的好处，包括鼓励实验、设置原则作为风险管理的一部分，并以小步骤开始应用人工智能，逐步扩大规模。最后，讨论了人工智能如何改变企业运营，尤其是在人力资源部门，通过优化投资、应对复杂环境和满足员工对于个性化、定制化体验的期待。

10:01

🌐 人工智能在人力资源管理中的应用

这一段探讨了人工智能如何改变人力资源管理的方式，尤其是通过实现全天候服务和处理简单查询来提高效率。IBM利用AI聊天机器人处理了年度150万次的对话，显著提高了服务效率和员工满意度。这种自动化不仅提高了响应速度，还使HR专业人员能够专注于更高价值的工作，促进了职业发展。文章还提到了其他潜在的人工智能应用，如在晋升流程中节省大量时间的自动化工具。总的来说，人工智能的应用使得人力资源管理更加高效、个性化，同时也为HR专业人员提供了更高级别的工作机会。

15:02

👥 人工智能、自动化与人性化文化的融合

最后一段总结了关于人工智能、自动化技术如何与人类文化相融合的讨论。强调了以人为本的设计原则和伦理道德在人工智能应用中的重要性。通过采用这种方法，IBM创建了一个既安全又包容的工作环境，促进了技术和人类劳动力的和谐共存。讨论还涉及了人工智能工具如何为员工提供价值，通过自动化繁琐的任务来提高工作效率和满意度。总之，人工智能的实施应以增强人类智能、保持道德原则和以人为本的文化为核心，从而在企业中创造正面的变革。

Keywords

💡人工智能

人工智能是一种可以模拟、延伸和增强人类智能的技术。视频中讨论了IBM如何利用人工智能来改进人力资源管理,例如实现24/7客服支持、自动回答常见问题等。

💡增强人类智能

人工智能的目标不是替代人类,而是增强人类智能。视频提到人工智能应该被称为“增强智能”。IBM的人工智能工具让员工腾出更多时间从事创新和创造性工作。

💡人际协作

人机协作对成功应用人工智能至关重要。视频中提到人工智能不应该作为决策者,而是辅助业务决策。IBM的原则是过程中始终有人参与。

💡实验

实验和迭代是成功应用人工智能的关键。IBM鼓励各部门从小地方开始实验人工智能,获得反馈,然后扩大规模。

💡聊天机器人

IBM为员工和管理层实现了一个聊天机器人,回答常见问题,大大提高了用户满意度,节省了人力成本。

💡流程自动化

人工智能可用于自动化业务流程,提高效率。视频中举了一个晋升流程的例子,通过自动化省下了1.2万小时的工作时间。

💡决策支持

人工智能可以从不同渠道汇总相关数据,支持业务决策过程。视频中提到这可应用于人才生命周期中的各个环节。

💡包容性

运用人工智能,IBM创建了一个安全、包容的工作环境。视频中提到他们有一套人工智能原则,确保公平性、透明度等。

💡员工体验

人工智能改进了IBM员工的体验,提供了定制化、个性化的服务,满足了他们的期望。

💡人才发展

在IBM,人工智能的加入提高了人力资源从业人员的层级,他们可以从事更高价值的工作,带来职业发展。

Highlights

IBM是一家拥有250,000多名员工的公司,他们都在参与人工智能领域的工作

人工智能的发展是一个渐进的过程,不是一下子就会发生的,员工需要有机会接触和实验新技术

IBM有一些人工智能的核心原则:人工智能只是增强人类智慧的辅助,而不是决策者

人工智能可以减轻员工的枯燥乏味的工作,从而让员工有更多时间进行创新和创造

企业需要有实验精神来获得人工智能带来的最大利益,同时也要有原则作为防护栏杆

人工智能可以24/7为员工提供支持,大大提高了员工的满意度

Transcripts

[Music]

hi everybody I'm Ray Juan with

constellation research and today I have

the pleasure to be here with nicool

lamro the chief HR officer of IBM hello

great to be with you Ray hey this is a

very interesting time we are at a point

where AI automation human labor are all

coming to a close of trying to figure

out what's next where do we go forward

and you're one of the most dynamic

companies going through this change so

let's start with the first question here

real quick what's going on with

reskilling AI automation like how are

you handling that and especially given

the number of employees remind everybody

how many people you have in the

organization so Ray this is a great

question because as you say there's a

lot going on in the technology space

around Ai and people tend to focus on

the technology aspect of it but there is

so much to focus on when you think about

reskilling how it's going to impact the

workforce here at IBM we have over 2

50,000 ibmers participating in what we

call the AI Revolution they may be

building products or helping clients

with it or even the internal staff

functions they're practicing using it

how can it re-engineer their processes I

think the important thing to think about

when you think about reskilling on the

AI space in general is it's not big bang

it's not going to just happen overnight

what you've got to think about is how do

you give people the opportunity to play

with the technology experiment with the

technology and experience it and then

over time you're going to see them

building skills no and it's crazy right

we're seeing like in every business

process in every organization there are

four things going on when do do

intelligent automation when do we

augment the machine with the human and

that's probably the most important job

like like why do you make an exception

right why did you break the rules why

did you do it differently right and

these systems are learning from us and

then of course when do you augment the

human with the machine so we can make

faster decisions and then every

organization is trying to make that

important decision when do you add the

human touch so I think this is really

important and you know again the

technology itself is pretty amazing but

thinking about when and where to use it

and when you don't use it I think are

equally important business decisions

here at IBM we have some really clear

principles about AI in the workforce AI

in the workplace the first one is is

that AI is meant to augment yes human

intellig and I know we've heard this

said before if I could go back in time I

would not call it artificial

intelligence I would call it augmented

intelligence and I think that is a key

tenant for us here the second thing that

I think is really important principle

for us at IBM is when we're using AI in

our internal processes AI is never a

decision maker no so you have so human

in the loop is Key Human in the loop is

really really key and I think that's an

important part we also believe that data

in in ins sites belong to the Creator so

again this is not about AI running wild

it is also not about us learning from

data that could be proprietary or your

competitive advantage and so as we think

about those processes those are some

principles that we have that are pretty

key here you that's really important

right you've got built-in AI ethics

you've got some really interesting

principles about working with machines

and Automation and Ai and that makes it

a very very safe environment and also a

very inclusive environment I I think

it's really true and you know you talked

about principles so we we talked about

some of these core tenants that we have

about AI not being a decisionmaker but

regardless of where you're using AI we

often think about some other principles

you have to have one is robustness the

robustness of the models this is what

makes them scalable this is what makes

them stand the test of time as the

models are working are they learning

from the right data sets yes

explainability mhm transparency yep

really really key do you know where the

data is coming from do you know what

it's doing so Lage veracity so important

we also think about things like um is it

fair so much is talked about in uh AI

around biases and how does that get

built in and so these principles for us

are really key as we're using it as

we're experimenting with it and also

building trust with our users that then

are at the end of this process oh I

really like this mindful approach and I

think it's really important that you

have a mindful approach now let's talk a

little bit about AI tools right and how

these tools are adding value to the

workforce because you know there A lot

of times we work on things that are so

boring so monotonous right you're like I

wish I had something to help me with

this or sometimes it's really hard to

find things and you're wishing like oh I

wish I had someone to help me find

something or give me institutional

knowledge and putting that into place oh

I'm so glad you asked the question this

way because as you know there's a lot of

negative maybe even doomsday perspective

out there about AI is it going to take

human jobs what's going to happen and as

I talked about I believe and we believe

at IBM that AI is actually going to be a

net job creator for exactly the reason

that you talked about what AI is going

to do is it is going to take away the

monotonous the administrative the rot

parts of people's jobs to allow more

time for Innovation for cre creativity

for the things that add business value

so this is about humans having more time

to do those things which is eventually

going to just be very good for business

yeah no I agree with you and and we're

definitely seeing the opportunities for

people to actually take the time to

think and things they wouldn't be able

to do before and we also have a lot of

cases where we're not finding enough

workers right or in countries where

population the population Dynamics are

shrinking as people age so a lot of new

opportunities been created there so

what's needed from Enterprises today to

ensure that they get the most from this

Ai and AI experience as we augment

intelligence in humanity the first thing

is you have to be prepared to experiment

so you have to be open to try things

there are going to be places where you

try to put AI in and it's a huge benefit

there going to be places where you try

to put AI in and it doesn't make that

much of a difference so we are in this

experimentation phase but the second

piece of this and that's really

important is you balance risk within

experimentation is you've got to have

these principles that we've talked about

what are the guard rails what do you

want the AI to do what don't you want it

to do particularly for HR leaders but

also for some other lines of Business

Leaders when we've thought about other

technology

revolutions they've been big platform

place they have been technology that

we've put into our processes that cost

several million dollars that might be a

two or threee implementation

and what's happening now with AI is I

think about it a little differently

rather than kind of buying the whole

house you can experiment lines of

business with small blocks and you can

try one thing at a time so this start

small see what works and scale it is one

of the power that the AI tools are now

giving you and I think that's also

extremely important no I love that uh

definitely check experimentation don't

stay in the background like test it out

um don't do it without principles

because that's really important because

you need that as your guard rails and do

it in bite-sized chunks yeah I think

it's really important and and then again

for line of Business Leaders don't

forget to get some Advocates try things

in pipelines again AI right now is

rarely going to be something that you

can just start using Enterprise ride

right away you're going to have to build

that momentum you're going to have to

have the models learn from each other

you're going to have to make sure that

you're putting it at the right Pro part

of the process

and so as you're doing that

experimentation build Advocates along

the journey with you get feedback from

your users about what is really

unlocking value or not and then scale so

how is AI then changing the Enterprise

in general oh from my perspective and I

think this is true for a lot lot of line

of business owners there are really

three things that are hitting us

particularly in the HR department one is

we're being asked to make sure that

we're making optimal investment ments

for every dollar that you spend are you

getting the best return Y the second

thing that's happening is the

environment that we're operating in is

getting more and more complex so you can

see how those first two things are

actually in conflict with one another

and then finally in the workplace

employees are expecting consumer grade

customizable personalized experim

experiences so all three of these things

are hitting us here in the the workplace

and just as you said AI is our ability

to unlock all of that how are we going

to make sure that we are using human

Talent where human Talent is needed the

most that's how you're optimizing AI is

also allowing human talent to deal with

very complex situations by giving you

information that you need real time and

the automation that you talked about is

exactly what is giving our employees

those custom customizable experiences

well then that means the HR function is

changing as well because of AI what are

you doing in that area we're doing a lot

in this area and you know just just a

couple examples as we think about it as

we are servicing our employees and

managers typically we would have done

this in very traditional ways we would

have assigned maybe HR business partners

to certain managers to meet with them

oneon-one or for our employees we would

have had call center support that they

would have to engage in with and what we

were hearing from our employees and

managers is is there an ability for us

to get 24 by7 support oh yeah again it's

hard to have you're a global company yes

exactly so 24/7 is 24/7 it is really 247

so how do you get that around the clock

service the other thing that we were

hearing from managers and employees were

things like there are some questions

that I actually don't need a human to

answer that you know just very quick

what's the vacation policy can I take

vacation very quick easy answers they

don't necessarily need a human to answer

that but there are times when they

needed an HR professional I'm about to

go out on maternity leave is everything

all set oh yeah I'd like to move to a

new job can somebody advise me on what

to do those types of questions required

human support but what was happening in

our organization was the very basic

question questions were taking a lot of

time of humans that they couldn't get to

the higher order questions and so we put

in an AI chat bot using Watson assistant

of course Watson X of

course and uh that is now the first part

of the interactions with all employees

and managers so that means all the

people that was that were answering

those questions the same monotonous Road

questions people were waiting for that

they're now being serviced and now

elevated to the next level of support

absolutely and so here's the way I would

describe it a couple things happened as

we did this so first of all that askhr

digital layer the AI enabled assistant

is handling 1.5 million conversations a

year which you probably couldn't have

done with the contact centers like that

before no way and it's real time they're

not waiting in the queue right so

they're getting that information real

time The

NPS for our digital layer has gone up to

plus 35 o that's really high it is very

high and in some processes it's as high

as plus 70 wow and it's because they can

get that information real time but as

you said they're also getting to the

experts faster so that digital layer is

now routing them to the tier 2 human

tier when they do have one of those

questions that we want handled by a

human to put this in context for those

listening here like that's a really high

net promoter score like really really

high especially and in HR that is really

high so absolutely and this is a journey

that we've been on for for a couple

years but it's not just about managers

and employees for the profession itself

we've also seen a ton of value as you

said dealing with a net promoter score

of plus 35 or plus 70 is a pretty good

work environment to be in but the other

thing that we're seeing is that for a

lot of these processes the average level

of an HR professional has gone one full

grade or ban in our world so they are

doing that higher value work um that is

bringing kind of more career progression

for them fun HR I guess we're moving the

nine box a little bit differently now

exactly yeah so no this is great so that

means all this stuff is coming in place

so how should other chros change their

approach given that there's all this

Technology Innovation in front of them

and AI is playing one of those parts of

the role the culture is also something

that you're talking about here and more

importantly as well changing the way

people work I think about kind of two

key entry points if I think about the HR

function one is this digital assistant I

think it can add a ton of value in an

organization for basic Q&A basic

transactions basic queries and it might

be how you then want to tier your

support model a second area of Entry if

you think that's not for you is actually

around automation which you referenced

before

every HR process has a lot of processes

that underpin the daytoday talent life

cycle yeah whether it's payroll or

Talent acquisition or benefits or

careers or

compensation and so thinking where you

might want to input to get better

leverage some forms of automation one

thing that we hear from HR professionals

a lot is that as they run Talent Cycles

maybe it's a promot cycle they have to

take data from a lot of different

sources to make sure that we're making

the best decisions it's a great place to

start with automation where automated

intelligent automation can actually

bring in data from different sources and

surface it up to H our professionals and

managers and you're right for every

organization or even industry it's going

to be different right that hire to

retire to Boomerang cycle is going to

play a different play absolutely we

recently put in Watson or orchestrate

our automation tool into a promotion

process here at IBM and in one promotion

process that typically would have taken

about one quarter we saved 12,000 hours

just by some very simple automation now

can we do that with space optimization

when you move

offices maybe that could be another use

case you can write the check and we'll

see what we can do no that's very very

cool well hey this has been a wonderful

discussion with you we're looking at the

intersection of all these AI

advancements automation but remember

it's all about being human and really

building that around the culture people

have to be comfortable with it you have

to think about this with humans first a

good ethical approach in terms of your

AI design but more importantly Don't Be

Afraid get started right absolutely just

get started Nico thank you very

[Music]

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