Q = red and green life
A = Bai Jiaqi.
Kate Dylan, Global Partner of Mercer Consulting
Q: With the development of artificial intelligence technology, many financial practitioners are also worried about their careers. In your opinion, in 5- 10, what jobs in the financial circle will be completely unemployed or forced to transform?
A: According to our research, only 20% of the management in China think that their company can successfully retrain an employee who needs to be transformed. But with the "robot consultant", it does not mean that human beings will be unemployed.
The fact is that some professions will indeed die out, such as bookkeeping and data processing functions will be replaced by artificial intelligence in the near future. And those tasks that need to deal with contextual information, such as making judgments and communicating with customers. Still need us humans to do it.
The development of science and technology will promote the prosperity of retail and trade industries, which will also generate more demand for financial services, but also have higher requirements for personalization. Personalization may be the key to make a company stand out in the market, which is something that no one has to do.
Q: According to a survey report earlier this year, as many as 30% of Wall Street people who have worked for 6- 10 years and have not passed the MBA admit that they will seek job-hopping or career change in the short term. Do you think the financial industry will also face a "talent crisis"?
A: The role of science and technology is to destroy the inherent foundation and promote changes in various industries, so the phenomenon you mentioned has appeared in many industries. But no matter what industry you come from, people in the workplace can improve themselves through further study and training to adapt to a new era. Only with the mentality of constantly absorbing new things, rather than blindly avoiding changes in the industry, can such talents survive.
Through investigation, we found that most people like to work in a company that constantly seeks innovation. This shows that as long as people can conform to their own nature in the workplace, they will be more motivated to stay in a position for a long time, and vice versa.
Q: The same survey I mentioned above also mentioned that financial practitioners on Wall Street value whether a job is "flexible". Coincidentally, the "odd job economy" has become popular in western countries in recent years. Do you think it has a future in the financial industry?
A: Our research also points out that the "flexibility" pursued by many people is actually the desire for work-life balance. If the traditional working mode can't satisfy them, many people will turn to the "odd-job economy", which is also rising in China. However, the financial industry is traditionally known for its stable work and economic security, so I am not optimistic about the development prospects of the odd-job economy in this industry.
According to the feedback from the survey, only two-thirds of the financial practitioners said that they were outsourcing contract workers, while the figures for the pharmaceutical industry and the high-tech industry were 90% and 8 1% respectively. This also proves my view that the "odd-job economy" is incompatible with the core values of this industry.
Q: IT and finance are undoubtedly the hottest and most profitable industries in China. However, the demand of financial companies for talents in programming technology, data processing and algorithm analysis is also increasing day by day, and there is competition for talents with the IT industry. From the perspective of human resources experts, what advantages and disadvantages do you think the financial industry has in this competition?
A: We predict that there will be a shortage of IT talents in China, which is very consistent with what you mentioned. Today, computer technology is very popular, and in the future, big data, algorithms and artificial intelligence will be popularized in business activities. The financial services industry has also increased its investment in this area, which has established a career development framework for these talents and provided important positions. At the same time, the financial industry is seeking transformation through Fintech, and this emerging frontier industry has also given IT talents more high-quality career development options.
Q: We have noticed that many world-class financial services companies, such as Goldman Sachs, have begun to use social media to publish recruitment information. At the same time, the report also mentioned that Goldman Sachs launched an online evaluation system to find talents with specific skills. So do you think that one day, financial companies will generally evaluate candidates by their performance on social media?
A: In fact, many companies are already looking at the social media behavior of candidates during the recruitment evaluation, and we also think that this will become one of the criteria for background review. More advanced evaluation systems have also begun to "describe" an object by mining social media information. Perhaps this impression of "passive input" will eventually replace the traditional background assessment tools.
However, because not everyone has left a mark on social media now, and this requires strong third-party intervention and supervision, it seems that this evaluation method cannot completely replace the existing methods in the short term.
Q: As the saying goes, experience is everything. I think the development of science and technology can not be separated from the help of human experience. There is an idea in the report that makes me feel very interesting: in the future, human employees can be used as mentors to train AI employees. Can you elaborate on it?
A: In order to improve the complexity of machine learning algorithms and artificial intelligence, it is necessary to provide a large amount of data with contextual information, which requires experienced human employees to constantly "train" or even "shape" a new generation of artificial intelligence.
At the same time, artificial intelligence often "calculates" some unexpected and biased results. We also need experienced human beings to see this wrong scientific principle clearly and find out the idea of "treatment".