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Srishti-2019   >>  Article - English   >>  Artificial intelligence and future job thoughts

Artificial intelligence and future job thoughts

Written By: Bhavini .B. Shah
Company: Cognub Decision Solutions Pvt. Ltd

Total Votes: 192

Whoever controls the strongest artificial intelligence controls the world.
Artificial intelligence is the most important technology of the 21st century.
It is therefore important to understand global ambitions and movements. So far, the first wave of digitization has developed without much government influence. Although there are now plans to break Google's monopoly (USA and Europe), for example by imposing European fines on Google and Facebook, politics is lagging behind the market by over a decade. As far as AI is concerned, for the first time in recent history I have observed a multitude of initiatives, strategies and actions by dozens of governments around the world - with very different goals and approaches.

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Artificial intelligence is and remains an issue that politicians and administrations of all nations have to deal with. AIs are relevant for climate protection and economic policy. AIso influence the governance of domestic industry, the security and privacy of citizens.

Economic power through artificial intelligence

While politics provides the framework conditions for research, financing, education, data, promotion and regulation, in the medium term AIs must be developed by companies and brought onto the market. First of all, national interests have to be taken into account. These include, often with their own agenda and independently, global corporations with their own AI research and AI products. In my view, Google, Amazon and Microsoft are global leaders. The Chinese Internet giants Alibaba, Baidu and Tencent are also relevant players.

There are two types of companies: Those that develop and sell AI as a core product and those that use AI to complement their value chain. Either way, any company active today has to deal with artificial intelligence. On the one hand, AIs can replace existing business models, and on the other hand, they can be integrated into countless company-internal processes: Accounting, controlling, production, marketing, sales, administration, personnel management and recruiting. By the way, this is the primary driver of applied artificial intelligence: reduce costs and maximize profits. And, of course, it's also about control. Every AI used takes over activities that were previously performed by humans. Often, after a while of training, the AI is faster, more efficient and cheaper than the human being was before. People become ill, they need holidays, food and sleep. They have to be entertained, quit or retire. AIso work 24/7 and do not demand a wage increase. The more companies use AIs, the more independent they become of human labour.

Data is a competitive advantage

The foundation of any artificial intelligence is data. We therefore need data on several points. First of all, we need data for the research and training of narrow artificial intelligences. The more digital your business model is, the more data you have. For this reason, marketing leaders (Google, Facebook), software companies (Salesforce, Microsoft) and e-commerce retailers (Zalando, Amazon) have been heavily involved in AI for years. Some banks also recognized the trend early on. Therefore Goldman Sachs and J.P. Morgan have already recruited thousands of employees with a focus on machine learning and data science. Those who have their own data can achieve an enormous competitive advantage. Those who have no data have to collect, store and evaluate data. However, this is where the different national data protection laws come in, which is why Europe is at a disadvantage. GDPR/DSVGO may indeed have the good intention to create a European data internal market, but currently form an enormous location disadvantage for Europe. The fear of the regulation paralyzes whole industries. Personal discussions with clinics and doctors showed me that the health industry no longer shares any data. This literally costs human lives, because this obstacle is detrimental to health research and life-prolonging algorithms. This is just one example among many. Uncertainty about data is paralysing our entire European industry. For fear of penalties, data is not collected at all. We are creating a culture of data anxiety at a time when data is actually our strength. Europe is the most important data market in the world, but we are wasting our potential. China, on the other hand, is the extreme opposite. The state helps with a lively exchange and centralization of data. In addition, the population has fewer concerns about the free handling of data. De facto, privacy no longer exists in the 21st century. Every digital action is measured and stored. However, we Europeans are sticking to an old ideal.

Artificial intelligence start-ups are the giants of the day after tomorrow

Start-ups are essential for any economy because they take on two essential functions of an ecosystem. Start-ups are drivers of innovation. These young companies are often more courageous, faster and more flexible in developing new products than established companies. Backed by the capital of venture capital funds and business angels, start-ups take high risks in the expectation of extraordinary success. Although 95% of start-ups do not survive the first 5 years, the entire ecosystem benefits from them.
Companies can buy new products and innovations through acquisitions.
Former employees find new jobs and transfer their knowledge.
Investors and founders learn and take their knowledge with them into new projects.
Perhaps the young company will survive the 5-year threshold. It secures financing (from seed to IPO), gains talent, grows, develops products for which customers pay, scales and becomes a corporation. Facebook, Google, Apple, Amazon, Uber - all started out as start-ups and are now dominant market leaders.
Charles-Édouard Bouée, former CEO of Roland Berger, said at the 2018 Rise of AI conference that the next wave of trillion-dollar companies will mainly be AI companies.
This won't work without start-ups. That's why we need to encourage building start-ups.

Without infrastructure there is no artificial intelligence

By infrastructure I mean not only the availability of data but also the necessary computing and performance capacities.
NVIDIA used to be known for their graphics cards among gamers. Today, NVIDIA is one of the leading manufacturers of GPUs, which are increasingly used for AI applications. Google, Intel and many other companies are very active in the development of new AI chips in various forms.
At the same time, Microsoft, AWS, Google and IBM are expanding cloud capacity around the world to meet growing demand.
While China will focus strongly on 5G, which is critical for real-time AI applications and the networked industry, Europe will not play a leading role in this technology issue either.

Artificial intelligence must be financed

The development of artificial intelligence is expensive.
Top AI researchers are rare and receive salaries of up to €300,000 per year.
Data must be collected, sorted and labelled. Developing AI models takes time for experiments, mistakes and new methods.
AIs need data, must be trained and educated.
These costs are borne by companies, start-ups, investors and also the state.
China has understood this and is investing over 130 billion euros in the Chinese AI market. Provinces such as Beijing, Shanghai and Tianjin are each investing tens of billions in local AI industry.
In the USA, Google, IBM, Microsoft, Amazon, Facebook and Apple have already invested over 55 billion dollars internally by 2015.
Without money, there is no artificial intelligence.
And once again Europe is too stingy to invest in the future.
A comparison of the orders of magnitude: In 2018, the German Bundestag had budgeted as much as € 500,000 for AI funding. A further 500 million is planned, but the funds are not yet available.
Progress will not succeed in this way.
At the same time, China is financing 400 new chairs for AI. To date, we have seen nothing of the 100 new professorships planned under the German AI Strategy.

Where does Europe stand in the global AI arms race?

As I mentioned earlier, Europe is currently losing the competition for the leading AI nations.
While Europe is still considering whether to compete at all, China, the US, Israel, the UK and Canada are already competing for data, markets and talent.
Our problems in Europe are homemade, they are the result of our inertia, lack of vision and ambitions.
There is a lack of money for education. Not only are our schools and universities underfunded, but so is the education labour market. Our children are not learning enough about digital skills. Our students rarely take AI-relevant subjects. Our working population lacks retraining opportunities that also meet the needs of the growing digital industry.

The transfer of research results to industry is sluggish. Results either disappear into the drawer, or the IP transfer is in bureaucratic terms a horror, especially for young companies and spin-offs.
Our European AI start-ups are significantly underfinanced. Those who currently need money from investors must market e-bikes and e-scooters, but they should not include technology. The more complex the product, the more difficult it is to get capital. The simpler the business model, the faster the accounts are filled.
Although many talents from Asia and America want to work in Europe, it has become bureaucratically complicated. Since the wave of refugees, the offices have been overwhelmed. It is almost impossible to hire talented AI developers from Iran, Russia or China. There is currently a spirit of rejection rather than openness in Europe.
Europe lacks a single strategy. Countries such as Finland, Sweden, the Netherlands or France have their own AI strategies and, moreover, a great deal of ambition. Germany, in particular, is blocking a common European approach and thus possible success.
When I was with the European Commission in 2018, a Bulgarian researcher said that she would be happy if her country had a plan at all. According to her, entire sections of Europe are significantly worse off than we are in Western Europe.
I am not saying that politics must solve all our problems. Companies still have to build products, founders have to start start-ups, VCs have to finance these start-ups and researchers have to do research.
But politicians can support us with a clear strategy. It can build up regulatory structures instead of inhibiting them. It can create incentives for investment and act as a role model. And it must be a matter of course for politicians to take care of the education of pupils, students and qualified further education in general.
Europe is marked by power struggles, egoism and technology phobia.

Global challenges for humanity

But Europe is only part of the world and must adapt to a global power order.
Therefore, there are many challenges for the growing artificial intelligence industry.
First of all, there is the issue of data protection. Which standard will prevail? Europe has currently set clear standards that will ensure that companies develop their AIs outside the EU.
Will we completely abandon data protection in the future and have Chinese free movement of data? Or will the European system prevail in the medium term?

Artificial intelligence needs supervision

Furthermore, all governments must think about the regulation and supervision of artificial intelligence. AIs are increasingly influencing the media, industry, education, security, military and financial markets. There is therefore a need to regulate how artificial intelligence (and the companies that design it) is controlled. 
For example, the Chinese company Squirrel AI helps millions of students to develop individual learning content that matches their learning pace and skills. But who in Europe would control and supervise these AIs in terms of content and subject matter? I cannot imagine that thousands of local education ministries are currently in a position to do so. 
Authorities must therefore recruit the necessary specialist staff, develop concepts and put them into practice. This takes time and should happen sooner rather than later.

It needs an artificial intelligence ethics framework

Artificial intelligences make decisions every second and almost every decision has an ethical component. AI ethics and AI morality are inseparable from the research and application of artificial intelligence. 
Artificial intelligence can prevent - or reinforce - prejudice, racism, corruption and sexism. 
Therefore, an AI ethics framework is urgently needed. At the upper level, every cultural area (often organized in states) has to deal with this.
This social discourse must be actively started and conducted. Currently, AIs are being developed without controlled morality. It is up to the developers to decide how the machines act later. But society itself should have this sovereignty over right and wrong. 
Therefore, every nation, every state system and every ethnic group must begin to discuss their own AI ethics frameworks.
The same applies to companies. Every company needs an AI ethicist, just as there are data protection and equality officers. The AI ethicist ensures that the data is unbiased and that the AIs do not discriminate against anyone. 
This also requires AI ethics frameworks in companies that are based on social values and also reflect the corporate culture in the code.

The rise of strong artificial intelligences

We also need to address the issue of growing intelligence and the influence of artificial intelligence. 
OpenAI recently received another billion dollars from Microsoft for research into General Artificial Intelligence (AGI), in addition to the billion dollars from Elon Musk. 
There is a reason why Musk, Zuckerberg, Hawking and Gates warn against artificial intelligence. Siri may still be stupid today, but could surpass your intelligence in 10 years. 
Artificial intelligences become smarter, more knowledgeable, more capable and faster every day. Contrary to our biological nature, there are no limits to the AIs.

The machines are energy hungry

Another global challenge is the energy requirements of the machines. While our brain needs as much electricity as a light bulb, AI applications are extremely energy-intensive. 
So if we want to maintain technological progress, we need to solve our energy problem. Otherwise, not all people will be able to live long and healthy lives.  
We therefore need energy sources that are sustainable and scalable.

A society without work?

Furthermore, as a society, we must start talking about our work. We Germans in particular are afraid that the machines will take away our jobs. 
Personally, I think it would be great if machines could relieve me of work. 
But the machines won't steal your job. I estimate that 50% of today's human activities are carried out by machines in 20 years because they are cheaper and faster. 
This development is therefore a good thing, at the same time it is a challenge. 
There will be many new activities that we do not even suspect today. These will include AI kindergarten teachers, AI trainers, AI ethicists and AI controllers.
It is therefore important that we think about how we can retrain those people who perform tasks today that will be performed by machines tomorrow. 
It will be the greatest retraining in human history. Some people will not make this change, what happens to them?
Others will use freedom and redesign their lives. 
I hope that in the future the meaning of life will not be work, but the joy of life. I hope that we get to the point where everyone works because they want to, not because they have to. Let the machines do the work that nobody wants to do. And let us finally pay better the people who take over important social activities such as bringing up our children, teaching pupils and caring for us in old age. 
Either way, we need a radical new social model, because the earth does not need 10 billion philosophers, artists, entrepreneurs or programmers.

How do we distribute wealth?

Probably not the last, but a crucial challenge is the question of how to distribute wealth. 
If fewer and fewer people are needed for the same productivity, companies' profits will increase. But companies are often in the hands of a few selected families and funds. Today, 40% of all publicly listed companies in the US are already owned by four gigantic funds. 
This trend will result in very rich people becoming much richer. A few chunks of this wealth will then fall to the administrative class (lawyers, bankers, entrepreneurs, investors) and hardly anything remains for the remaining 99% of the population.

Civil war or a carefree life?

With artificial intelligence, this trend will become more extreme. I fear that in 30 years around 100 people will control 90% of the world. We are not just talking about money here, but about access to the machine code and thus to the control of the global economy, the military and information. 
And what if the majority of people lose their current importance for the system, namely to work and consume? Does the idea of the Club of Rome then become real and we reduce ourselves (involuntarily) to 500 million people? 
AI makes it possible.
So if we want to prevent a civil war, prosperity must be distributed beforehand. In any case, so much of it that no one has to fear hunger, homelessness and poverty anymore. 
There are many approaches and ideas. Let us please discuss them further, such as the basic income and liquid democracy.  
Let us ensure that we live in a world where the machines serve all of humanity.

Friend or foe?

Artificial Intelligence (AI) has the potential to improve productivity, efficiency and accuracy across an organization.

With AI continuing to be a prominent buzzword in 2019, businesses need to realize that self-learning and black-box capabilities are not the panacea. Many organisations are already beginning to see the incredible capabilities of AI, using these advantages to enhance human intelligence and gain real value from their data. 
As there is increasing evidence demonstrating the benefits of intelligent systems, more decision-makers in the boardroom are gaining a better understanding of what AI can really offer. Research conducted by EY explains “organizations enabling AI at the enterprise level are increasing operational efficiency, making faster, more informed decisions and innovating new products and services.”

Today In: Innovation

The first companies employing AI systems across the board will gain competitive advantage, reduce cost of operations and remove head counts. Whilst this may be a positive from a business perspective, it is obvious why this a worry for those working in roles at risk of displacement. The introduction of these technologies will likely trigger an issue with unions and job security due to the substantial operational changes.

Although AI will affect every sector in some way, not every job is at equal risk. PwC predicts a relatively low displacement of jobs (around 3%) in the first wave of automation, but this could dramatically increase up to 30% by the mid-2030’s. Occupations within the transport industry could potentially be at much greater risk, whereas jobs requiring social, emotional and literary abilities are at the lowest risk of displacement.

A positive future with artificial intelligence

Many businesses and individuals are optimistic that this AI-driven shift in the workplace will result in more jobs being created than lost. As we develop innovative technologies, AI will have a positive impact on our economy by creating jobs that require the skill set to implement new systems. 80% of respondents in the EY survey said it was the lack of these skills that was the biggest challenge when employing AI programs. 
It is likely that artificial intelligence will soon replace jobs involving repetitive or basic problem-solving tasks, and even go beyond current human capability. AI systems will be making decisions instead of humans in industrial settings, customer service roles and within financial institutions. Automated decisioning will be responsible for tasks such as approving loans, deciding whether a customer should be onboarded or identifying corruption and financial crime. 
Organisations will benefit from an increase in productivity as a result of greater automation, meaning more revenue will be generated. This thus provides additional money to spend on supporting jobs in the services sector.

How to take advantage of AI

Due to the vast array of jobs that could be impacted by AI, it is fundamental to address the potential pitfalls of these technologies.

·         Business need to overcome the trust and bias issues surrounding AI by achieving an effective and successful implementation that makes it possible for everyone to benefit.

·         Governments must ensure that gains from AI are shared widely across society to prevent social inequality between those affected and unaffected by these developments. For example, this could be through increased investment into training.

·         With the additional cost-savings from implementing AI systems, employers should also focus on upskilling their current employees.

To properly leverage the power of AI, we need to address the issue at an educational level, as well as in business. Education system needs to focus on training students in roles directly associated to working with AI, including programmers and data analysts. This requires more emphasis to be put on STEM subjects (science, technology, engineering and mathematics). Also, subjects centered around building creative, social and emotional skills should be encouraged. Whilst artificial intelligence will be more productive than human workers for repetitive tasks, humans will always outperform machines in jobs requiring relationship-building and imagination.

Artificial intelligence will change our world both inside and outside the workplace. Instead of focusing on the fear surrounding automation, businesses need to embrace these new technologies to ensure they implement the most effective AI systems to enhance and compliment human intelligence.

Future Job Thoughts

Technological advancements have had a direct impact on jobs, creating new ones and eliminating the redundant. Today, technology and digitisation have made the lives of consumers simpler, while enabling businesses to leverage advanced tools like AI and Machine Learning to build better products and services. A recent Gartner report noted that the next couple of years will be a defining period as AI will be a major job-creator.

The report stated that, by 2020, AI will generate 2.3 million jobs, exceeding the 1.8 million it is expected to replace. It also revealed that the number of new jobs created by AI and AI-powered tools will reach 2 million by 2025.

A large number of sectors and enterprises that have integrated AI are using the technology primarily for Big Data Analytics through Machine Learning tools. In the digital age, gigabytes of data are created each second by millions of consumers. In order to reach out to customers in a more efficient way, data-driven personalisation is a key element of effective customer service.

Hence, businesses are going to great lengths to ensure they are equipped to use this deluge of data to their advantage—for delivering a higher quality of services and products to customers, and staying ahead of competitors.

Thus, AI has come to play a critical role in key processes like sales and marketing. From powering recommendation engines of Google, Netflix, Amazon that push personalised content towards consumers, to performing complex functions like data and cybersecurity, financial trading and fraud detection, AI can perform a range of functions.

But the application of AI and Machine Learning is largely limited to functions like collecting and processing data, and hence a skilled human workforce is essential for creative tasks and roles that demand human skills, and qualities like emotional intelligence. As of now, less than 5% of occupations are entirely automated, and about 60% comprise 30% tasks that can be automated.

It’s more likely, then, that humans will continue to guide machines, and dominate jobs that require essential skills such as interpersonal relations, emotional range and complexity, dexterity, and mobility, as opposed to the idea that machines will make us redundant.

Upskilling for new-age jobs

Constant learning and skill-building will play a critical role in preparing global workforce to deal with the impact of technology on jobs. Investing in human capital is important for companies to develop skills in employees who are required to work with modern technologies.

The current workforce, both employed and unemployed, should have access to reskilling and upskilling opportunities, and businesses must identify the skills that employees must have, and provide them with the right training. According to a survey by Capgemini of 1,000 organisations, 71% companies have pro-actively initiated reskilling programmes for employees to provide them with skills that equip them to work with AI and automation.

The current and future workforce must have better access to lifelong learning opportunities, which is critical to adapting to an ever-evolving technological and business ecosystem. Simultaneously, we need to fundamentally revise our school and higher education curricula and teaching systems to emphasise more on practical skills and knowledge.

These measures will be crucial to enable both the workforce of today and tomorrow to realise its full potential, and taking the country to the next stage of economic growth.

Jobs AI can do better than humans

While AI is making exponential advances year after year, the popular media often like to exaggerate what it is capable of for the sake of eye-catching headlines and anxiety-inducing news soundbites.

The truth is, while technology is making great strides in simplifying and automating some work, the truth is that many of these tasks are actually much simpler and fewer than you might think.

For example:

1.      Empathy and communication: While AI is being used in medical applications to do things like more accurately detect diseases on a scan, I certainly wouldn't want to get a robocall to break the news that I have cancer. Even though we are making strides towards affective computing, we are a long way away from any technology that can genuinely recognize human emotions and respond to them appropriately, so any job that requires empathy like primary care physicians, caregivers, and therapists are unlikely to be outsourced to technology any time soon.

2.      Critical thinking: I love the old science fiction shows where the human asks the computer what they should do in a terrible situation, and the computer predicts a 99 percent probability of failure — but the human goes and does the thing anyway, and usually succeeds. To me, it's a beautiful metaphor for the fact that, no matter how advanced our AI may be, we still need a human to make judgments and critical decisions, even to "go with our gut," in certain situations. A more contemporary example might be that law firms are employing AI to help identify relevant documents in legal cases, but we still need a human judge to adjudicate a decision. (A computer judge and jury would be an entirely different sci-fi horror story in the making.)

3.      Creativity: Computer programs are good at spitting out a number of options, but they're not necessarily good at providing quality of creative choices. While AI can technically produce food, music, or art, the results can be… Well, less than inspiring. We've probably all seen the funny lists of AI-generated recipes or paint colors or even inspirational quotes. Any job that requires true creativity, such as writers, engineers, inventors, entrepreneurs, artists, musicians, etc., are probably safe for a long while based on these results.

4.      Strategy: In business especially, we're beginning to see a lot of automation of marketing practices and the like. For example, I can tell a program to send a Tweet for me at a particular time of day, every day. And while these can be huge time savers, the automation tools are just that: tools. They don't provide the overall strategy needed to give the individual tasks meaning and relevance. Any job that requires strategic thinking is likely to be safe, and improving your skills in that area can help robot-proof your job.

5.      Technological management, installation, and upkeep: Until the robots have robots of their own to install and maintain them, humans are going to be needed to design, plan, install, manage and maintain any robotics, technology, or AI systems. This takes us back to my first point about understanding what technology is capable of; the more familiar you are with the technology, the more valuable you will be in helping implement and maintain it.

6.      Physical skills: While robots are being created that can do increasingly tricky things, like make your morning latte, there are still a significant number of physical skills robots haven’t mastered. Additionally, we humans seem to love to watch each other accomplish incredible physical feats (the World Cup is just one example). So if you have any amazing physical skills, from crafting to sport, you’re also safe for now.

7.      Imagination and vision: Finally, one quality I can't quite imagine a robot or AI ever possessing is just that: imagination. The way AI currently works is by taking existing data and making logical inferences based on parameters we give it. Imagination and dreaming are merely not programmable skills. Activists, entrepreneurs, visionaries, thought leaders, authors, speakers and others have a distinct advantage over technology in this field, and that isn't going to change any time soon.

10 Jobs That Are Safe in an AI World


Psychiatry, social work, and marriage counseling are all professions that require strong communication skills, empathy, and the ability to win trust from clients. These positions require keen emotional intelligence, professionals who are capable of communicating with patients, consoling patients in times of trauma, and providing long-term support. These are all weaknesses for machines.


Dexterity is a challenge for AI. Physical therapy, as well as chiropractic and massage therapy, involves applying very delicate pressures with our hands and being able to detect minute responses from a client’s body. In addition, therapists of all kinds are tasked with customizing care for their clients, avoiding accidentally hurting a client, and providing ongoing, professional, person-to-person interaction. These essential features of therapy make this profession inherently humanistic, and not fit for AI.

Medical care

The healthcare industry is expected to grow substantially due to increased income, greater health benefits, AI lowering the cost of care, and an aging population who require more care. Many of these factors will foster a symbiotic relationship between humans and AI, which can help with the analytical and administrative aspects of healthcare. Healthcare professionals like doctors and nurses will still be necessary to carry out the features of care fueled by compassion, support, and encouragement.

AI-related research and engineering

As AI grows, there will naturally be a jump in the number of AI professionals. Gartner Research Company estimates that in the next few years, these increases will outnumber the jobs replaced. However, as AI technology improves, some entry-level AI positions will also become automated. AI professionals will need to keep up with the changes caused by AI just as, in recent years, software engineers have had to learn about assembly language, high-level language, object-oriented programming, mobile programming, and now AI programming.

Fiction writing

Storytelling requires one of the highest levels of creativity, and one which AI will have difficulty emulating. Writers ideate, create, engage, and write with style and beauty. The success of a great work of fiction lies in original ideas, interesting characters, an engaging plot, and poetic language. All of these essential components of writing are hard to replicate through algorithms. While AI will be able to write social media posts, suggest book titles, and perhaps even imitate writing styles, the best books, movies, and plays will ultimately be written by humans, at least for the foreseeable future.


AI will be a great tool for teachers and educational institutions, as it will help educators figure out how to personalize curriculum based on each student’s competence, progress, aptitude, and temperament. However, teaching will still need to be oriented around helping students figure out their interests, teaching students to learn independently, and providing one-on-one mentorship. These are tasks that can only be done by a human teacher. As such, there will still be a great need for human educators in the future.

Criminal defense law

Top lawyers will have nothing to worry about when it comes to job displacement. reasoning across domains, winning the trust of clients, applying years of experience in the courtroom, and having the ability to persuade a jury are all examples of the cognitive complexities, strategies, and modes of human interaction that are beyond the capabilities of AI. However, a lot of paralegal and preparatory work like document review, analysis, creating contracts, handling small cases, packing cases, and coming up with recommendations can be done much better and more efficiently with AI. The costs of law make it worthwhile for AI companies to go after AI paralegals and AI junior lawyers, but not top lawyers.

Computer science and engineering

A McKinsey report shows that the number of engineering professionals like computer scientists, engineers, IT administrators, IT workers, and tech consulters will increase by 20 million to 50 million globally by 2030. But these jobs require staying up-to-date with technology and moving into areas that are not automated by technology.


Science is the ultimate profession of human creativity. AI can only optimize based on goals set by human creativity. While AI is not likely to replace scientists, AI would make great tools for scientists. For example, in drug discovery, AI can be used to hypothesize and test possible uses of known drugs for diseases, or filter possible new drugs for scientists to consider. AI will amplify human scientists.


Good managers have essential human interaction skills including the abilities to motivate, negotiate, and persuade. They can effectively connect with employees on behalf of companies. More importantly, the best managers are able to establish a strong workplace culture and value system through their actions and words, which elicits hard work from their employees. While AI may be used to manage performance, managerial work will continue to be carried out by humans. That said, if a manager is merely a bureaucrat sitting behind a desk and giving employees orders, they will likely be replaced by other humans.



AI is at the centre of a new enterprise to build computational models of intelligence. The main assumption is that intelligence (human or otherwise) can be represented in terms of symbol structures and symbolic operations which can be programmed in a digital computer. There is much debate as to whether such an appropriately programmed computer would be a mind, or would merely simulate one, but AI researchers need not wait for the conclusion to that debate, nor for the hypothetical computer that could model all of human intelligence. Aspects of intelligent behaviour, such as solving problems, making inferences, learning, and understanding language, have already been coded as computer programs, and within very limited domains, such as identifying diseases of soybean plants, AI programs can outperform human experts. Now the great challenge of AI is to find ways of representing the commonsense knowledge and experience that enable people to carry out everyday activities such as holding a wide-ranging conversation, or finding their way along a busy street. Conventional digital computers may be capable of running such programs, or we may need to develop new machines that can support the complexity of human thought.