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  • Why we must bridge the skills gap to harness the power of AI

    Font: World Economic Forum Jan 3, 2024 The Artificial Intelligence (AI) revolution is upon us, with AI becoming a pervasive force in our daily lives. While AI brings tremendous potential benefits — from diagnosing illness to predicting earthquakes — the possible disruption from the AI revolution could also be significant. As the rate of AI adoption increases, humans are essential to guiding the technology’s implementation and usage of these technologies. Before we can fully embrace this revolution, we have an obligation to reskill our talent to use these technologies effectively, equipping them to succeed in today’s environment. Executives estimate that up to 40% of their workforce may need to reskill as a result of implementing AI or automation over the next three years. This is largely because humans need diverse skills — from technical proficiency to human understanding and adaptability in their thinking — to work most effectively alongside AI. While this percentage seems daunting, the demands on today’s workforce present a unique and exciting opportunity to empower a new group of people to enter desired, skills-oriented jobs in the digital economy. We need to rethink our approach to reskilling to achieve this goal while ensuring the skills of our workforce match the pace of technological advancement. Invest in human capital First, we must stop fixating on whether AI will impact our lives and start managing the elements within our control. While the ubiquity of AI has caused fear of these technologies overtaking human ability, this is not yet the case — and may never be. Human capital is a much more important asset than ever before. As Dr. Chris Mason, director of the WorldQuant Initiative for Quantitative Prediction, and I discuss in our book, The Age of Prediction, humans and machines will continue to have a symbiotic relationship. Prediction is an innovative tool for advancement but requires human collaboration to enhance its outcomes. As we move into the future of technology, we should increasingly focus on the value of what we are doing: bringing opportunity to talent and using technology to strengthen our workforces. Integrate reskilling as a change management initiative Research shows that few companies to date have taken the call to action for reskilling seriously. Companies have become so preoccupied with filling immediate vacancies that they focus less on internally developing talent for future roles. While CEOs say hiring is the most important thing they do, many companies are entirely disengaged from the process and feel it is their biggest challenge. With constantly evolving demands on jobs and skills, we cannot solely rely on hiring. The only way to fully prepare our organizations for the future is through upskilling and reskilling. Leaders need to start viewing reskilling as an organizational change management initiative — preparing workforces for lasting change and offering them the skills required to thrive in a rapidly evolving job market. This transformation goes beyond just training employees. It underscores the importance of creating an organizational context — across leadership, managers and employees alike — in which reskilling will be embraced to maximize success. Doing so might create new opportunities for better-paying and more skilled roles. Leverage new technology to support education We are entering a new era for education, made possible by the commoditization of AI. The growth of information and data available to us means there is an ever-increasing opportunity to learn more and to facilitate learning opportunities. Online learning platforms are expected to grow 19% over the next four years. We need to lean into this trend. With AI breaking down barriers to quality education, simplifying interfaces and providing varied learning pathways, organizations should embrace the accessibility of reskilling programs. Let’s use the widening availability of education platforms to our advantage by building from within, partnering with an academic institution or establishing public-private partnerships. Embedding these kinds of reskilling programs will help ensure a seamless transition toward a more agile, tech-savvy and future-ready workforce. Online learning platforms can help organizations worldwide close the AI skills gap. Image: Statista Market Insights. Closing the AI skills gap Organizations that recognize the value of human capital while embracing advanced technologies will be most prepared for the future of work. Empowering employees with opportunities to reskill will help them better leverage AI tools, helping to drive business value, improve efficiency and shape the future of success. Implementing a cultural shift around reskilling will help organizations accelerate this change. Only then will we be able to more fully understand and harness the potential of AI.

  • Máquina desenvolvendo máquina: o impacto da GenAI na criação de softwares

    Fonte: McKinsey & Company 22 de Novembro de 2023 Inteligência artificial generativa virou assunto de grande parte das discussões estratégicas de uma organização. Em um estudo lançado recentemente pela McKinsey, estima-se que as aplicações da GenAI vão movimentar até US$4,4 trilhões na economia mundial todos os anos — e grande parte desse valor vem de ganhos de produtividade em engenharia e desenvolvimento de software. Mas como a máquina pode ajudar a desenvolver máquinas? Montamos um laboratório com desenvolvedores de diferentes nacionalidades e analisamos os impactos em produtividade de algumas ferramentas de IA generativa na geração, otimização e documentação de códigos. O grupo testado conseguiu executar tarefas em até metade do tempo versus o grupo controle. Os resultados são impressionantes. Mas, assim como na Fórmula 1, em que um carro sem motorista (ainda) não é capaz de vencer um GP, com a GenAI é preciso ter “pilotos” bem treinados que consigam manejar e acelerar a máquina ao máximo. Velocidade máxima Escrever um novo código com a ajuda da GenAI levou, em média, metade do tempo, assim como a documentação da funcionalidade de um código para manter a capacidade de manutenção. Já a refatoração, que é a otimização de um código existente, foi concluída em um tempo 30% menor do que o original. Além de mais rápidas, as tarefas utilizando ferramentas de GenAI também performaram bem no quesito qualidade – ou seja, a velocidade não sacrificou a boa entrega. Inclusive, a qualidade do código em relação a bugs, a capacidade de manutenção e a legibilidade foram ligeiramente melhores no código assistido pela inteligência artificial. Além da velocidade, satisfação Os benefícios encontrados alcançam também aqueles profissionais que estão por trás das máquinas. É que, no caso da GenAI, a pesquisa revela melhoria expressiva na experiência do desenvolvedor, o que, por sua vez, pode ajudar as empresas a reter e motivar seus melhores talentos, um desafio frequentemente relatado por lideranças de tecnologia. Os participantes do estudo foram duas vezes mais propensos a relatar satisfação geral e estado de flow – algo que pode ser descrito como a capacidade de imergir numa tarefa. Isso porque, segundo eles, as ferramentas utilizadas foram capazes de automatizar o trabalho pesado, permitindo que realizassem atividades mais satisfatórias e que acessassem mais rapidamente informações na hora de solucionar um desafio. É como deixar de guiar o volante de um caminhão 1982 e passar a manejar uma macia direção elétrica. Três marchas variáveis A IA generativa está preparada para transformar o desenvolvimento de software de uma forma que nenhuma outra ferramenta fez. Mas, se o carro não vence a corrida sozinho, aqui vão três variáveis fundamentais para o bom funcionamento das engrenagens: Complexidade da tarefa: em afazeres que os desenvolvedores consideravam de alta complexidade devido, por exemplo, à falta de familiaridade com uma estrutura de programação necessária, o ganho de tempo foi menor, de menos de 10%. Tempo de experiência do desenvolvedor: profissionais mais juniores, com menos de um ano de experiência, levaram de 7% a 10% mais tempo com as ferramentas de GenAI do que sem elas. A tecnologia pode fazer muito, mas as conclusões sugerem que as ferramentas são tão boas quanto as habilidades dos engenheiros que as utilizam. Fator humano: os desenvolvedores participantes do estudo interagiram ativamente com as ferramentas para alcançar a qualidade descrita, sinalizando que a tecnologia contribui mais para aumentar o potencial dos desenvolvedores, e não substituí-los. E, por isso, experiência e habilidade são muito relevantes para os resultados. Como dirigir? Qual é o impacto das novas conclusões para as lideranças e como avançar a partir delas? Alguns insights apontam caminhos. Um deles é assegurar uma combinação de treinamento inicial e apoio contínuo aos desenvolvedores. Para aqueles com menos de um ano de experiência, a pesquisa sugere a necessidade de uma formação em princípios básicos. Para os mais experientes, a formação deve ser focada nas interações com as ferramentas e em como manter um olhar crítico, sabendo diferenciar uma recomendação ruim de um código ou uma alucinação, por exemplo. Estimular que desenvolvedores mais sêniores dividam as melhores práticas com os mais juniores também é fundamental. Ainda no quesito talentos, com o aumento da produtividade e a redução do tempo dedicado a algumas tarefas, os líderes terão de se preparar para realocar parte de sua força de trabalho em atividades de maior valor e desenvolver novas habilidades nas equipes. Aqui, as empresas precisam redobrar a atenção: por ser um mercado novo, avaliar a produtividade dos profissionais é um desafio necessário a ser enfrentado – como uma pista encharcada na Fórmula 1, que escancara os gaps de habilidades entre pilotos. Ainda há uma longa estrada À medida que a tecnologia evolui e se torna perfeitamente integrada às ferramentas no ciclo de desenvolvimento, espera-se ainda mais velocidade e qualidade no processo. A GenAI significa um ponto de inflexão no caminho da busca pela excelência. Os motores ainda estão esquentando, mas têm um torque que pode levar as equipes ao topo do pódio. SOBRE O(S) AUTOR(ES) Marina Mansur é sócia e líder de Leap by McKinsey – digital business building, no Brasil. Rafael Siqueira é sócio e líder de Build by McKinsey na América Latina.

  • CONVIVENDO COM ROBÔS

    Fonte: JAPAN HOUSE A mostra retrata aspectos particulares do desenvolvimento de robôs japoneses e oferece ao público brasileiro a oportunidade de refletir sobre a convivência com eles de maneira amigável, já que ao cotidiano japonês eles já estão mais do que incorporados. Período: 14.11.2023―31.03.2024 Terça a sexta-feira das 10h às 18h Sábados, domingos e feriados das 10h às 19h Custo: Entrada gratuita, inscreva-se. No universo da ficção científica, os robôs são retratados como amigos e parceiros de trabalho, que interagem com os seres humanos e reproduzem emoções, já que estão integrados à vida cotidiana. Os conhecidos friendly robots, ou robôs amigáveis, em português, projetados para se relacionarem com os humanos de maneira simpática, segura e colaborativa, são o tema da exposição ‘Convivendo com robôs’. Um futuro de coexistência Com o objetivo de tornar familiar uma possível coexistência futura com tais elementos, a mostra apresenta 11 robôs em 4 categorias: colegas de trabalho, companheiros, comunicativos e os que ajudam os humanos. “São robôs que já existem e são usados na prática. Não são de ficção, com o objetivo de aumentar a eficiência ou como protótipos em desenvolvimento”, declara o curador Zaven Paré, pesquisador do segmento de tecnologia e robótica. Muito mais do que apenas robôs A exposição destaca principalmente os exemplares que existem como companhia com ênfase na comunicação não-verbal, possuindo, inclusive, a função de expressão emocional, ao invés de um dispositivo apenas de comunicação. Projetados com inteligência artificial e sensores sofisticados, o que lhes permitem compreender e responder às necessidades e expressões humanas de forma intuitiva, os robôs amigáveis têm sido empregados em estabelecimentos comerciais, escolas, hospitais, casas de repouso e até no cotidiano doméstico, tornando-se verdadeiros assistentes pessoais ou até membros da família. “Acredito que o HAL deve ganhar muita atenção do público adulto, principalmente. Ao observar um exoesqueleto é possível criar uma conexão instintiva, pois as pessoas se projetam envelhecendo - e este robô pode funcionar como um suporte importante no futuro de cada indivíduo”, ressalta o curador. A mostra apresenta os exemplares aibo (Sony Group Corporation), BIG CLAPPER (BYE BYE WORLD Inc.), Gatebox (Gatebox Inc.), HAL – Hybrid Assistive Limb (CYBERDYNE Inc.), LOVOT (GROOVE X, Inc.),necomimi (NeuroSky Co., Ltd. /neurowear), NICOBO (Panasonic Entertainment & Communication Co., Ltd. | ICD-Lab Toyohashi University of Technology), PARO (National Institute of Advanced Industrial Science and Technology), Pepper (SoftBank Robotics Group Corp.) e Qoobo (Yukai Engineering Inc.). “O presente no Japão nos conta um pouco sobre o futuro em todo o mundo, por exemplo, a solidão no contexto do envelhecimento populacional. O Japão é um laboratório. Alguns desses robôs demonstram como é possível motivar e interagir. São robôs empáticos, que trazem apelos emocionais e expressões universais como o ato de bater palmas ou um olhar mais expressivo.”, comenta Paré. A exposição mostra ainda uma linha do tempo sobre a história do robô no Japão e no mundo, considerando a realidade e a ficção científica. Destaque para o ancestral dos robôs: o autômato servidor de chá Chahakobi Ningyô. Típico do Japão, ele aparece em romances populares no período Edo e é fruto do progresso técnico da relojoaria, figurando na origem da concepção de máquinas industriais. Exposição interativa Os robôs aibo, BIG CLAPPER, gatebox, HAL, LOVOT, NICOBO, PARO e Qoobo, em exibição na mostra atual, podem interagir e surpreender com suas habilidades únicas - importante verificar a disponibilidade com a equipe de orientação durante a visita. Já o Pepper, um dos primeiros robôs humanoides capazes de expressar emoções, e o necomimi, um dispositivo que utiliza as ondas cerebrais para expressar sentimentos antes de palavras serem ditas, contam com sessões específicas de interação.

  • How to Reskill Your Workforce in the Age of AI

    Font: Here How will AI affect businesses and employees? It’s the million-dollar question, and according to Harvard Business School’s Raffaella Sadun, the answer will depend on how well an organization connects the new technologies to both a broad corporate vision and individual employee growth. One without the other is a recipe for job elimination and fewer new opportunities for all. Luckily, she points out, we are early in our AI journey, and nothing is predetermined. Smart leaders don’t need to understand every technicality of AI. But they do need to identify the best use cases for their specific business and communicate a clear strategy for reskilling their teams. For this episode of our video series “The New World of Work”, HBR editor in chief Adi Ignatius sat down with Sadun, who wrote the HBR article, “Reskilling in the Age of AI”, to discuss: How leaders should use GenAI to augment their own decision making, without entrusting it to make the actual decisions. Even in the age of AI, the top management skills will be a mixture of technical (“hard”) and social (“soft”) skills. Those who excel will comprehend their organization’s complexity while communicating a clear vision to all employees. Handling change management when everyone is uncertain about the future and regular employees are especially fearful. “The New World of Work” explores how top-tier executives see the future and how their companies are trying to set themselves up for success. Each week, Ignatius talks to a top leader on LinkedIn Live — previous interviews included Microsoft CEO Satya Nadella and former PepsiCo CEO Indra Nooyi. He also shares an inside look at these conversations —and solicits questions for future discussions — in a newsletter just for HBR subscribers. If you’re a subscriber, you can sign up here. ADI IGNATIUS: Raffaella, welcome. Insight Center Collection The New World of Work Previous episodes RAFFAELLA SADUN: Thank you so much. It’s a pleasure being here. ADI IGNATIUS: I want to talk about your HBR article on re-skilling in the age of AI. Let’s start at a high altitude. How dramatically do you think workplaces will be transformed as AI technologies take hold? RAFFAELLA SADUN: It’s important to distinguish between the potential impact of this technology and what the reality will be. The potential is very high. As we’ve learned from past technological transformation, the possibility is that these technologies will change occupations radically. In fact, there are several estimates that tell us that maybe a huge percentage of the US population will be affected, for example, as occupations will be affected by these technologies. What’s very interesting about AI in particular is that it has the potential of having an impact on white-collar jobs and high-skilled jobs, which typically have been insulated from past technological revolutions. The part where we come back to reality is that at the end of the day, what happens will be a function of the adoption process. And the adoption process is typically very messy, as we’ve seen in other technological revolutions. It depends on figuring out how to integrate these technologies in the workflow. And it also depends on the incentives to adopt, whether people will accept these technologies as their everyday companions in their work. From what we know from past technological revolutions, it can take a while and it’s going to be a bumpy ride before we can really think about the revolutionary impact often mentioned in the press. ADI IGNATIUS: I know you can’t possibly know the answer to this, but I’m interested in your thoughts. Even the technology industry is split as to whether the widespread adoption of AI, generative AI, you name it, will eliminate jobs or will somehow create new jobs as we collaborate with machines. Do you have a view on that as you’re starting to see this play out in companies? Is it a net creator of jobs, subtractor of jobs, what’s your guess? RAFFAELLA SADUN: That is the million-dollar question. What’s going to happen at the end of the day depends on what firms’ strategies and organizational responses are. Let’s first say that not every firm will be actually adopting these technologies. Again, we’ve seen it in the past. There will be a lot of heterogeneity. And those that do have basically two ways of reacting to the technology, shaping the technology adoption. One will be the lazy way. And this is people, like Daron Acemoglu who have talked about this in other outlets, where essentially they’re going to substitute whatever workforce they can with new technologies without really changing their production processes, their organizational processes. That would be potentially complicated. There would be elimination of jobs without the creation of new opportunities. Then there is a second pathway that I find very exciting. Not everybody will get there, but I am pretty certain that some firms already are rethinking their workflows, and they’re rethinking their organizational processes in such a way that these technologies create new tasks, new opportunities, and potentially new jobs. I’m sorry to give you an answer that is not definitive, but it depends. The critical point is that it depends on what firms do. There is nothing that is predetermined at this point. ADI IGNATIUS: Let’s get back to the re-skilling question from the perspective of managers. How should we think about our workforces? Are we essentially now competing for external tech talent that is skilled in these new technologies? Or can we plausibly think about retraining an existing workforce to handle this challenge? RAFFAELLA SADUN: Look, in practice, firms are constantly doing both things at the same time. They’re sourcing talent from external labor markets, and I think to various degrees of commitment and resources, they’re also investing in training. What’s interesting is that the external workforce option becomes a little bit tricky these days for a couple of reasons. Some are related to the tightness of labor markets, which make sourcing external talent more costly. But also specific to AI and these new technologies is the fact that these technologies are effective only to the extent that they’re well-integrated with the specific use case. It’s not clear that somebody who is hired from the external labor market who doesn’t really know the production process would be best placed to adopt these technologies in this specific workflow of the organization. Two things: one, the cost, and the second the benefits of having external talent are somewhat changing. That’s what we’ve seen and what we document in the article, a newer attention towards solutions that are much more focused on internal talent, and not just upskilling internal talent but also re-skilling, which means giving them training that allows the workforce to jump from one occupation to the other. ADI IGNATIUS: Generative AI is a piece of this puzzle. It’s got us thinking, as a media company, as a learning company, how it creates opportunities, how it disrupts us. I figure that’s playing out through most companies now. Do you think we even know what the use cases are, let alone how to adapt our workforce to what those may be? RAFFAELLA SADUN: I think it’s very early-stage, to be honest. There are the estimates that I was mentioning before of this potential transformational effect of AI on occupations and jobs, typically based on taxonomies of occupations where you can break down an occupation in multiple tasks, and then there is an inference that says, well, these tasks seem to be amenable to AI and this doesn’t and that’s how we come up with these very large estimates of the potential impact of the technologies. When it comes to the reality, of course, even if an occupation is the same in principle, it can be very different across different firms. One of my favorite examples: I have a student here in my executive program that told me how he adopted AI in this shoe manufacturing company. I won’t get into the details of what he did, but he really thought for two years about the specifics of the production process in his firm and then modeled the AI adoption based on what he was doing and what was needed. This is a case where we are not talking about just getting a computer out of the box and plugging it. There will be a lot of adaptation and this is what makes every prediction extremely unreliable at this point. ADI IGNATIUS: Let’s talk about internal re-skilling. How does a leader create a re-skilling program that works? Are there takeaways from companies that you’ve seen who seem to be doing this effectively? RAFFAELLA SADUN: There is a lot of enthusiasm, I think at a high level, about re-skilling, and we’ve heard of companies that truly believe in the opportunity of providing their workforce with training that really allows them to thrive in this era of technological changes. The reality, however, is a little different from the hype, and this is something that we are currently studying. The problem is that even a well-designed training program, we heard from companies, sometimes has really low take-up rates. There seems to be resistance from the perspective of the employees in putting themselves, if you like, in the mix and going through these training programs to change occupations. Also, there is resistance at middle-managerial levels. We’ve heard, for example, of middle managers that were very concerned about sending their own workers to get trained and especially trained to change occupation, very naturally because that’s how you lose your talent. If you send your workers to a training program, effectively, you’re not only losing the person while this person studies or gets trained, but you’re also potentially losing talent in the long run. This is just to say what we hear at the high level, what the very ambitious estimates of what re-skilling can do, from our interviews, appear to face a reality that is often quite different. ADI IGNATIUS: Sending your team, your high potentials, to learn new skills, to go off and do an executive education program, you always run that risk that you may be training them for the next job. I don’t know if AI is just another example of that or somehow a more dramatic problem. But it might be useful for people to hear. What kind of incentives or programs can you set up where you do the training, but you’re not simply preparing your employee to go work somewhere else where there’ll be in demand? RAFFAELLA SADUN: That is a risk that always exists, and the organizations we spoke with embraced that risk. If you live in fear that training is going to immediately make you lose your talent, that is probably not the best attitude to invest in these training programs. What we’ve heard that seems to work better are training programs that are first of all embedded in a company strategy. If you are able to articulate why going through a re-skilling or up-skilling program matters for the organization and what the rewards are that people are going to get out of these training programs within the firm, that already changes the salience of the training program and how people see themselves within the organization. This is one. Second is making sure for people that go through these training programs, they can see the benefits of training on their own skill. Sometimes we have the super well-designed programs, wonderful technology, but people don’t know what’s going to happen to their own career. Here we’re talking really at the personal level. What happens to me if I get trained and maybe I change occupation down the line? What is my career pathway? That clarity is often absent, and [clarity] is something that increases the chances of take-up and makes the training program more successful, not just in general, but within the firm. ADI IGNATIUS: I want to go to an audience question. This is definitional to provide context. This is from Olivier in Switzerland. What kind of AI are we talking about here? There’s AI and there’s GenAI. What do you have in mind when we’re talking broadly about AI? RAFFAELLA SADUN: When people talk about AI, there is this very broad definition. In the specific examples that I was mentioning before, I’m thinking about decision support systems. One concrete example would be AI used in the context of buying decisions for supply chain managers, for example. Another case could be decision support systems for clinicians, for physicians. These are types of technologies that can help in decision making, but then of course the type of applications that are out there right now are much wider than that, much broader than that. ADI IGNATIUS: On generative AI, ChatGPT and Bard and Bing, are you finding a use for that in your world, in your profession or even for your hobbies? Are you finding a use case for yourself for GenAI? RAFFAELLA SADUN: Absolutely. I’m an economist by training and machine learning has gradually permeated even what we do at an academic level. The type of information that we can now distill from unstructured data is just incredible with large language models. In fact, Adi, with colleagues, we actually digitized the Harvard Business Review archives, and thanks to this algorithm we were able to extract the type of topics and problems that HBR worked with throughout the course of its history. This is just one example the structuring of unstructured information that is a very immediate application of AI within my specific field of research. ADI IGNATIUS: Back to re-skilling, let’s talk about the employee perspective. We all know that people learn at different rates. You just have to expect that and figure out how to bring more people along. Not everyone will get there, but for employees who want to get there and feel like, “OK, I’m late out at the gate. I don’t really understand AI, I don’t understand Generative AI,” how do they prepare themselves for this transforming world? RAFFAELLA SADUN: Let’s first clarify that learning a new skill is scary. I don’t know the last time you learned a new software, for example, or a new way of doing things, [but] I can tell you that, especially as an adult, it’s not the easiest thing to do. Even harder is learning a new skill to get to a new occupation. I am an applied economist. If you ask me to become a macroeconomist tomorrow, I’d be scared. It’s hard. The first thing is choosing training programs that are high quality. There is so much noise right now in the training market. That’s actually a challenge. A little bit of due diligence clearly on what you do, but I think that most of the work is actually on the mindset that you have as you approach learning new skills. And in particular, I think what matters is understanding, trying to put yourself in a condition in which you know that you’re going to face moments of fear or moments of “I just cannot do this, it’s too much”. How about thinking about cohort models where you’re not alone in this learning process, learning in the flow of work. That’s what we heard also from the companies, to lower the frictions and the inevitable bumps in the road that you will find when you start learning a new skill as an adult. ADI IGNATIUS: A few questions have come in that build on this question of fear. This is a question from Donna, from Alabama in the US. What else can businesses do to communicate that, yes, there’s uncertainty, yes, there’s fear, but how can they help employees move along the path despite all of that? RAFFAELLA SADUN: We go back here to the importance of having clear strategic vision on how this training program fits within the company’s future and the future of the employees. That can go a long way towards alleviating some of the concerns and some of the uncertainty that employees face. Why are we learning it and what is the strategic imperative that is driving the investments in training? The second is, are you structuring the incentives and the responsibilities in the organization in a way that makes training not just an HR initiative that lives in its own silo, but it’s really embedded in the organizational fabric of the firm? For example, some of the companies that we speak with make training part of the managerial responsibilities. There are KPIs around not only how much you train yourself, but also how much your subordinates get trained. And these are all things that help with the alignment. It’s important to acknowledge that there is risk on the employee side and making sure that training is as frictionless as possible. For example, making sure that people are paid or they’re not just expected to get trained on Sundays or Saturdays, making sure that they have a clear career pathway, making sure that the incentives are aligned for today and the long run. ADI IGNATIUS: I have a question from Richard in Cape Town, South Africa, and it’s about company culture. As we bring in AI, how do we think about maintaining, strengthening, and evolving a healthy corporate culture, as we’re relying on machines to do more and more of what humans used to do? RAFFAELLA SADUN: This is a great question. To some extent, my expectation is that companies with a great culture are going to be the companies that are going to be able to make the most of new technologies. It’s not just AI. These are the companies where change is easier because you have a culture, you know what to stand for. Going back to employees’ perspectives, these are probably the companies where it’s easier to experiment and change. The other point that you’re making on the extent to which a company’s culture influences how the technology is used, I think that’s a really interesting one. Some of my economist colleagues are very concerned that companies’ cultures are not focused enough on making sure that technologies contribute to the growth of employees rather than just substitution. There is a vast heterogeneity out there. If you are a culture that invests in its employees, it’s important to think carefully about the ways in which you are presenting technologies, and you’re presenting opportunities for your employees to grow with the introduction of these new technologies. ADI IGNATIUS: You’ve written in the past about the evolving needs for skills in the C-suite. This is a question from Shadia in Massachusetts in the US. What kind of leadership skills do executives need in the age of AI? Not necessarily to master AI technology, but it is transforming and will transform the workplace. What are the leadership skills that CEOs and the C-suite need most in this transformative era? RAFFAELLA SADUN: This is a question that I think pertains not just to the use of technologies, but the emergence of knowledge based and complex organizations. Since many organizations are going this direction, the type of skills that matter are not just cognitive or strategic skills, like knowing what to do, or knowing in-depth a specific technology. It’s having the skill that is necessary to combine all the knowledge that exists in your company. If you have, for example, more technically savvy people, it’s your responsibility as a leader to find a way for these technically savvy people speak to each other and communicate with the other parts of the organization that may not be as technologically savvy. These are social skills that allow for this trading of expertise. The second piece is related to the soft skills, persuading, and helping people cope with change. What is difficult is to find this unique mix of both cognitive skills and social skills. These are the type of leaders that I expect to really thrive going forward. We see this already. We see that the demand for these skills has increased a lot over the past 20 years, this combination of social and technical skills. ADI IGNATIUS: As the editor of a magazine that writes about management issues, I’ve been heartened over the years to see you do research and write pieces that say good management actually matters. It actually contributes to higher productivity. Sometimes, oddly, we seem to undervalue the role of management. In the research you’ve done, in the writing you’ve done, what can managers learn from your findings to improve what they do? RAFFAELLA SADUN: It’s almost a definition of who I am, believing that management matters and that managers should have this clear in their mind. They are critical for a company’s performance, a company’s success. Now, the piece that my research has explored in the past is that sometimes even the best managers underestimate the importance of basic management practices. You want to think about complexity, you want to think about strategy. Of course, that’s all really, really relevant, but please also make sure that the basics of management are implemented in your firm. In the research that you were mentioning before, we find that actually there is quite a bit of heterogeneity in the adoption of basic management practices across firms and across a variety of countries and industries, and this heterogeneity really matters for firm performance. I think we offer different explanations of why that could be the case, but maybe starting to understand where you are and not underestimating the basics would be my advice. ADI IGNATIUS: We’ve talked about AI in mostly positive terms, in terms of how it can contribute to a company and to its productivity. There are also potential or actual downsides we’re seeing. This is a question from Debra from Ontario in Canada, but I think there’s several areas of potential concern. Thinking about deep fakes, hallucinations, the things AI can do that are inaccurate, that could set us astray, how do we safeguard against some of these downsides that we’re already seeing? RAFFAELLA SADUN: These are relevant questions. On the one hand, the cost of using these technologies has really decreased enormously, even over the past year. The wide adoption is not even a year old. As the cost of these technologies has decreased, my concern is that we would use these technologies blindly, without truly understanding that they are not oracles, and they’re not able to make complex judgements or complex reasoning. They are effectively a support system for, but not really a [replacement for] decision making. My advice is to think about the use case, and never trust something that just comes out of the box. Most of the cost in the adoption of these technologies will be in adapting them, and truly understanding these technologies for your own specific use case. On the one hand, the cost of accessing the basic elements of the technologies have been lowered quite a bit, but on the other hand, where I think people should really focus their attention is making sure that the adaptation is done carefully and is done in an iterative way, making sure that there are no hallucinations, but also making sure that you’re adding value to your production process rather than just adding a new fancy toy just for the sake of it. ADI IGNATIUS: That’s good advice. I want to talk to you about the transformation in the workforce that’s happened really because of the pandemic that caused us all to adapt. Many of us are still in a hybrid work environment. To what extent do you think that period, and what we learned from that period, has permanently transformed both the workplace and how we think about work, how we interact? What are the lasting takeaways from that moment? RAFFAELLA SADUN: There has definitely been a shift. We see it, for example, in job adverts that now include remote work options. I’ve done some work on this and you can see that there has been a big jump, especially during the pandemic months, in the extent to which companies that were not offering remote options or hybrid options now do that. Now, however, and again this is looking at the data, you also observe that there is tremendous heterogeneity across firms in the extent to which hybrid and remote jobs are being accepted in a post-pandemic world. What we are seeing is that what matters is not so much the location, but the extent to which the design of the job is complemented by other organizational choices. Just to give you a few examples, the documentation of work, ways of communication, ways of promoting people, even if they’re not in the office. ADI IGNATIUS: Having looked at technology and its effect on the workforce, I’m curious whether you are a techno-optimist or a techno-pessimist or absolutely neutral. We all make a choice as to who we are on that and maybe it amplifies who we are inside. But I’m curious, as you’ve looked into some of these technologies in the workforce, are you basically optimistic, pessimistic, neutral? RAFFAELLA SADUN: I’m an organizational economist, Adi, so the answer that I’m going to tell you is: everything will be different. What’s important for your listeners is that as these new technologies emerge, what we might see, what we’ve seen in the past, is a polarization of outcomes across firms. My expectation is that maybe on average we won’t see much or we would see something but not as dramatic, but we will see vast differences in the extent to which some firms are really able to click and figure out how to use these technologies for their own benefit. In the past, these firms have typically been the larger ones because there are economies of scale in technology, and then we will see other firms that just don’t get it. I would just be alert, not just on the average effects, but I would be very, very careful about this opening up between those that are at the frontier and those that remain behind. ADI IGNATIUS: Raffaella, we’re almost out of time, but I really want to thank you. Thank you for being on the show. Thank you for your thoughts. RAFFAELLA SADUN: Thank you so much for having me.

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