The manufacturing landscape is undergoing a profound transformation as robotics technology becomes increasingly accessible, affordable, and intelligent. Over the past several decades, robotics has evolved from basic automation to advanced systems integrated with artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). This evolution is reshaping production processes, workforce dynamics, and competitive strategies across industries worldwide. As manufacturers strive to remain competitive in a global marketplace, the convergence of digital technologies with robotics is proving to be a powerful catalyst for change. Data-driven insights, case studies, and expert analyses demonstrate that the integration of robotics not only enhances productivity and quality but also promotes sustainability and operational flexibility (International Federation of Robotics, 2023; McKinsey & Company, 2020).
An Early History
Historically, manufacturing automation began with the introduction of programmable machines in the 1960s. These early systems performed repetitive tasks with high precision, reducing error rates and increasing production speeds. Over time, technological advances have given rise to robots that are not only faster and more precise but also capable of learning and adapting to complex tasks. Modern manufacturing robots are now deployed across industries ranging from automotive and electronics to food processing and logistics. The rapid adoption of robotics is evidenced by global trends: the industrial robotics market is valued at over $16.5 billion, with more than 2.7 million robots in operation across factories worldwide (International Federation of Robotics, 2025; Technology Magazine, 2024).
Today’s robots are no longer confined to monotonous, high-volume tasks. Instead, they are increasingly designed for versatility. They now perform both high-mix, low-volume manufacturing as well as complex assembly operations, often working collaboratively with human operators. This transition is highlighted by the rapid increase in robot density—the number of robots per 10,000 employees—which has doubled globally in the last seven years, growing at an average rate of 5% annually in mature markets (International Federation of Robotics, 2024). Such growth not only reflects the technological advancements in robotics but also underscores the strategic necessity for manufacturers to embrace automation in order to remain agile and competitive.
The Role of AI
At the heart of this transformation is the integration of artificial intelligence. AI and machine learning empower robots with advanced data interpretation capabilities, enabling real-time decision-making, predictive maintenance, and adaptive learning. AI-equipped robots analyze complex datasets gathered from various sensors, optimizing production lines and facilitating the rapid adjustment to changing production conditions. For instance, advanced image processing allows robots to recognize patterns and adjust their workflows to reduce error rates and enhance efficiency (McKinsey & Company, 2020; Robotnik, 2025). This dynamic interplay between hardware and software is setting the stage for a manufacturing revolution where intelligent machines continuously refine production processes.
One compelling example of this integration is seen in the automotive industry. Traditionally reliant on robotics for welding, painting, and assembly, automotive manufacturers are now pushing the boundaries of automation. At the BMW factory in Cowley, Oxford, for example, robotic systems work in tandem with human operators on the Mini Clubman production line to boost efficiency while upholding high-quality standards (Alamy, 2023). Similarly, electronics manufacturers have adopted high-precision robotic arms for printed circuit board (PCB) assembly, achieving accuracy levels that significantly reduce defects (iStock, 2023). These case studies illustrate how robotics is not only enhancing quality and speed but is also opening new avenues for product innovation.
The current phase of robotic evolution is characterized by several groundbreaking technologies that are converging to redefine manufacturing. One such technology is the emergence of collaborative robots, or cobots. Unlike traditional industrial robots that operate in isolation behind safety barriers, cobots are designed to work directly alongside human workers. Their advanced sensors and simplified programming interfaces make them accessible even for small-to-medium enterprises (SMEs), ensuring that automation is not limited to large corporations (StandardBots, 2025; Robotnik, 2025). These systems are engineered with robust safety features that enable secure human-robot interactions, even in high-risk environments.
Digital Twins
Another transformative technology is the digital twin—a virtual replica of physical production systems. Digital twins allow manufacturers to simulate and optimize robotic operations in risk-free virtual environments before deploying them on the factory floor. This technology helps identify bottlenecks and potential failures in advance, significantly reducing unplanned downtime and maintenance costs (ESA Automation, 2025). When combined with AI, digital twin simulations enable continuous improvements in production processes, facilitating faster decision-making and more efficient resource allocation.
The integration of robotics with IoT is revolutionizing production lines by enabling seamless data exchange between machines. Modern manufacturing facilities are increasingly outfitted with interconnected systems that monitor performance in real time. Big data analytics from these systems provide critical insights into process inefficiencies, allowing manufacturers to implement predictive maintenance strategies that can reduce downtime by up to 50% (McKinsey & Company, 2020). Such data-driven approaches not only improve operational efficiency but also extend the lifespan of equipment, ultimately contributing to significant cost savings.
Adoption Trends
Global manufacturing is also witnessing regional variations in robotics adoption. In the European Union, for example, the robot density stands at 219 units per 10,000 employees—a figure that reflects steady growth and technological leadership among countries such as Germany, Sweden, and Denmark (International Federation of Robotics, 2024). North America follows with a density of 197 units, while Asia is experiencing the fastest growth, with regions such as South Korea, Singapore, China, and Japan leading the way. Notably, China accounts for approximately 52% of global robot installations, highlighting its pivotal role in shaping the future of industrial automation (Technology Magazine, 2024).
The transformative potential of robotics extends beyond the realms of productivity and efficiency. For many manufacturers, the adoption of robotics is also a strategic response to evolving market demands and environmental challenges. Modern robots are being designed with sustainability in mind. Innovations such as lightweight materials, energy-saving modes, and low-power actuators contribute to reduced energy consumption and lower carbon footprints. These eco-friendly designs are particularly crucial as industries strive to meet increasingly stringent environmental regulations and consumer expectations for sustainable production practices (World Economic Forum, 2021; ESA Automation, 2025).
Beyond technological advances, the economic implications of robotics adoption are far-reaching. Falling costs of robotic systems, driven by higher production volumes and improved software capabilities, have made automation more accessible for a broader range of manufacturers. This democratization of robotics has opened up opportunities for SMEs to implement advanced manufacturing solutions that were once the preserve of large multinational corporations (StandardBots, 2025). For example, Grupo Fortec, a Mexican manufacturer of construction materials, successfully replaced manual palletizing with an automated robotic solution, thereby increasing productivity while ensuring safer working conditions (Mitsubishi Solutions, 2023).
In addition to capital cost reductions, the economic benefits of robotics are amplified by improved operational performance. Robotics not only enhances production capacity but also reduces the variability inherent in manual processes. Automated quality control systems, which employ machine vision and sensor technologies, ensure consistent product quality while minimizing defects. This consistency translates to reduced waste, lower rework costs, and improved customer satisfaction—a critical competitive advantage in today’s fast-paced market (Forbes, 2022; McKinsey & Company, 2020).
Another significant benefit of robotics is the role they play in streamlining supply chain management. Automated systems are adept at managing inventory, tracking shipments, and even forecasting demand based on real-time data. This capability has become particularly vital in light of recent global supply chain disruptions. By reducing reliance on manual processes and human error, robotics contribute to more resilient and responsive supply networks, ensuring that production schedules remain uninterrupted even in challenging circumstances (StandardBots, 2025).
However, the integration of robotics is not without its challenges. The complexity of implementing advanced robotic systems, particularly in legacy manufacturing environments, remains a significant barrier. The initial investment required for robotics adoption, though declining, still represents a substantial commitment for many organizations. Additionally, the successful integration of robotics demands specialized skills for programming, maintenance, and system management. As a result, manufacturers must invest in comprehensive workforce training programs to ensure that employees are equipped to work alongside these sophisticated systems (Deloitte, 2022; StandardBots, 2025).
Cybersecurity also presents an emerging challenge as robotic systems become increasingly interconnected. With the integration of IoT and real-time data analytics, manufacturing robots are now potential targets for cyber threats. Ensuring robust cybersecurity measures is paramount to protect sensitive production data and maintain the operational integrity of automated systems. Manufacturers are therefore required to adopt comprehensive security protocols and continuously update their systems to mitigate potential vulnerabilities (Deloitte, 2022).
Transforming the Workplace
Workforce transformation is another crucial aspect of this technological revolution. Contrary to fears of job displacement, the adoption of robotics is reshaping the workforce by shifting human roles from repetitive manual tasks to more strategic, creative, and technical functions. By automating mundane operations, companies can reallocate human resources to tasks that require problem-solving, innovation, and critical decision-making. This evolution not only enhances overall productivity but also creates opportunities for new job categories in areas such as robot programming, maintenance, and data analysis (International Federation of Robotics, 2023; StandardBots, 2025).
One noteworthy example of workforce transformation is exemplified by Amazon. In its robotics research and development centers, the company has been testing human-like robot solutions capable of performing tasks traditionally associated with manual labor. These robots, developed in partnership with Agility Robotics, are designed to handle repetitive tasks such as shifting empty tote boxes, thereby freeing human workers to engage in more complex roles (Technology Magazine, 2024). Such collaborative efforts between human employees and robotic systems highlight the potential for automation to create a more efficient, safe, and dynamic work environment.
Looking to the future, several emerging trends are set to further accelerate the integration of robotics in global manufacturing. One of the most promising areas is the continued evolution of AI and machine learning. As algorithms become more sophisticated, robots will be able to learn from experience and adapt to new tasks with minimal human intervention. This will not only reduce the programming complexity but also allow for real-time optimization of production processes (Robotnik, 2025). The potential for what some experts refer to as a “ChatGPT moment” in physical AI could revolutionize the way robots are programmed, making them even more versatile and efficient.
Another transformative trend is the rapid growth of collaborative robots. These cobots, which are designed to safely share workspaces with human operators, are quickly gaining popularity across diverse industries. Cobots offer a unique value proposition by combining human creativity with robotic precision, thereby enhancing overall operational efficiency. Their simplified programming interfaces make them particularly attractive to SMEs, allowing even non-expert users to deploy advanced automation solutions (Robotnik, 2025; StandardBots, 2025).
Digital twin technology is also poised to play a significant role in the future of manufacturing robotics. By creating virtual replicas of production lines, manufacturers can simulate different operational scenarios, test modifications, and optimize processes without any physical risk. This capability not only reduces downtime but also provides a cost-effective means of innovation. When integrated with AI and real-time data analytics, digital twins facilitate continuous improvement, driving both efficiency and product quality (ESA Automation, 2025).
The integration of robotics with IoT further enhances the responsiveness of manufacturing systems. As sensors and connected devices collect vast amounts of operational data, manufacturers are able to implement predictive maintenance strategies that preemptively address issues before they result in costly downtime. This level of data-driven decision-making represents a significant leap forward in operational efficiency and reliability (McKinsey & Company, 2020).
Moreover, sustainability has emerged as a core focus in the development of robotics technology. Manufacturers are increasingly prioritizing eco-friendly designs that reduce energy consumption and minimize waste. Energy-efficient robotic systems, combined with advanced waste management solutions, are enabling companies to meet stringent environmental regulations while also achieving significant cost savings. In industries such as renewable energy, robotics is playing a pivotal role in the production of solar panels, electric vehicle batteries, and recycling systems, thereby contributing to a greener manufacturing future (World Economic Forum, 2021; ESA Automation, 2025).
In summary, the future of robotics in global manufacturing is defined by a convergence of advanced technologies, economic imperatives, and strategic workforce transformation. The integration of AI, collaborative capabilities, digital twins, and IoT is not merely an incremental improvement—it represents a fundamental shift in how production is conceived, executed, and optimized. Manufacturers that strategically invest in these technologies and address associated challenges such as cybersecurity and workforce adaptation will be well positioned to lead the next industrial revolution.
Key Takeaways
The integration of robotics into global manufacturing is transforming industries through enhanced efficiency, precision, and adaptability. The industrial robotics market has reached remarkable heights, with over 2.7 million robots in operation and a market value exceeding $16.5 billion. Advances in AI and machine learning are enabling robots to analyze data, predict maintenance needs, and adapt to complex tasks. Collaborative robots are redefining workplace dynamics by safely working alongside human operators, while digital twins and IoT-driven analytics optimize production processes and minimize downtime. Furthermore, these technological innovations support sustainability goals and drive economic benefits by reducing costs and enhancing product quality. Despite challenges such as implementation complexity and cybersecurity risks, the long-term benefits of robotics in manufacturing are set to redefine production methodologies and create new opportunities for workforce development.
Conclusion
The future of robotics in global manufacturing represents a transformative era that extends well beyond the automation of routine tasks. As robotics systems become more intelligent, adaptive, and collaborative, they are redefining traditional manufacturing paradigms by improving productivity, quality, and sustainability. Manufacturers worldwide are witnessing firsthand the benefits of integrating AI, digital twins, and IoT, which together create a dynamic, data-driven environment capable of rapid innovation and continuous improvement. The shift toward collaborative robots and environmentally responsible designs underscores the importance of balancing technological advancement with workforce transformation and sustainable practices. For industry leaders, the imperative is to invest in these technologies, redesign production processes, and develop the skills necessary for a future where human ingenuity and robotic precision work hand in hand.
This technological revolution is not only about achieving greater operational efficiencies—it is about reimagining the manufacturing ecosystem. By embracing the challenges and opportunities presented by robotics, manufacturers can drive long-term competitive advantage, foster innovation, and contribute to a more resilient and sustainable global economy.
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On April 5, 2025, Meta introduced three new AI models: Llama 4 Scout, Maverick, and Behemoth. Let's take a quick look at what each of them can do.
Scout: Efficient and Capable
Scout has 17 billion parameters and runs on a single NVIDIA H100 GPU. It has a large context window of 10 million tokens. This helps it handle long documents, summarize data, and process complex code.
It beats other models like Gemma 3, Gemini 2.0 Flashlight, and Mistral 3.1 in many tasks.
Maverick: Versatile and Strong
Maverick also has 17 billion parameters but uses 128 experts. It can understand both text and images together. It does better than GPT-4o and Gemini 2.0 in coding, languages, and long text tasks. It uses a method called Mixture of Experts to save computing power.
Behemoth: The Next Big Thing
Behemoth is still in training. It has 288 billion active parameters and 2 trillion total. Meta says it outperforms GPT-4.5 and others in math and science tasks. It might help train smaller models in the future.
Multimodal Features
All three models can understand text, images, and videos together. They use early fusion to combine these inputs. This can help in healthcare, content creation, and more.
Meta released these models as “open,” but there are limits. Big companies need permission to use them. Some people say this means the models are not truly open source.
RAG and Context Windows
Scout’s long context window may reduce the need for Retrieval-Augmented Generation (RAG). But RAG can still help when new or specific info is needed.
Key Points
Scout is efficient with a 10 million token context window.
Maverick is powerful and handles both text and images well.
Behemoth is huge and still in development.
All models use multimodal input and a Mixture of Experts setup.
There are questions about how “open” these models really are.
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Imagine a world where your doctor is assisted by a super-smart computer that can diagnose diseases faster than any human, or where your favorite video game is designed by an AI that knows exactly what you like. This isn’t science fiction—it’s happening right now, thanks to Artificial Intelligence (AI). From self-driving cars to virtual assistants like Siri and Alexa, AI is already changing the way we live, work, and play. But what does this mean for you, a teenager about to enter the workforce? The future of work is being reshaped by AI, and it’s going to look very different from today’s job market. As an advanced teen reader, you’re in a unique position to understand and prepare for these changes. This post will explore how AI is transforming industries, what it means for future careers, and how you can get ready for this exciting yet uncertain future.
AI is more than just a buzzword—it’s a powerful tool that’s revolutionizing industries across the globe. But it’s also raising important questions about the future of jobs, skills, and ethics. Will AI take away jobs, or will it create new ones? What skills will you need to thrive in an AI-driven world? And how can you, as a teenager, prepare for these changes? In this post, we’ll dive into these questions, backed by data, real-world examples, and expert insights. Whether you’re curious about AI or planning your future career, this guide will give you the knowledge and tools to navigate the AI-powered future of work.
Understanding AI: A Brief Overview
Before we explore how AI is changing the world of work, let’s make sure we’re on the same page about what AI actually is. Artificial Intelligence, or AI, refers to computer systems that can perform tasks that typically require human intelligence. These tasks include things like recognizing speech, making decisions, translating languages, and even creating art. One of the key branches of AI is machine learning, where systems learn from data and improve over time without being explicitly programmed. For example, when Netflix recommends a show you might like, it’s using machine learning to analyze your viewing habits and make predictions.
AI is already deeply embedded in our daily lives. Think about how you use your smartphone: from facial recognition to unlock your device to predictive text when you’re typing a message, AI is at work. But its impact goes far beyond personal convenience. According to a 2021 report by the World Economic Forum, AI could create 97 million new jobs by 2025, but it will also displace 85 million jobs. That means a net gain of 12 million jobs, but it also highlights the massive shift in the types of jobs that will be available (World Economic Forum, 2021). For teens like you, this means the future job market will be full of opportunities—but only if you’re prepared with the right skills and mindset.
AI’s Impact Across Industries
AI is not just changing one or two industries—it’s transforming nearly every sector of the economy. Let’s take a closer look at how AI is revolutionizing healthcare, finance, and education, and what that means for future careers.
In healthcare, AI is being used to improve diagnostics, personalize treatment plans, and even predict disease outbreaks. For example, AI algorithms can analyze medical images like X-rays or MRIs faster and more accurately than human doctors. A study by Stanford University found that an AI system could identify skin cancer with 95% accuracy, compared to 86.6% for dermatologists (Esteva et al., 2017). This doesn’t mean AI will replace doctors, but it does mean that future healthcare professionals will work alongside AI to provide better care. Teens interested in medicine should be prepared to embrace technology as a key part of their future careers.
The financial sector is another area where AI is making waves. Banks and financial institutions are using AI for everything from fraud detection to algorithmic trading. JPMorgan Chase, one of the largest banks in the world, developed an AI program called COIN that reviews legal documents in seconds—a task that used to take lawyers 360,000 hours (JPMorgan Chase, 2017). This kind of efficiency allows financial institutions to serve customers faster and more accurately. For teens, this means that careers in finance will increasingly require an understanding of AI and data analysis.
AI is also transforming education by providing personalized learning experiences. Imagine a tutoring system that adapts to your learning style, helping you master difficult concepts at your own pace. A 2020 study by the Bill & Melinda Gates Foundation found that students using AI-based math tutoring software improved their scores by 30% on average (Gates Foundation, 2020). As AI continues to evolve, future educators and students will need to be comfortable using these tools to enhance learning.
These examples show that AI is not just automating tasks—it’s enhancing human capabilities across a wide range of fields. For teens, this means that no matter what career path you choose, AI will likely play a role in your future work. The key is to understand how AI can be a tool to help you, not something to fear.
The Future Job Market: Opportunities and Challenges
As AI continues to advance, it’s natural to wonder: will robots take all the jobs? The answer is both yes and no. While AI will automate many routine tasks, it will also create new opportunities for those with the right skills. According to a 2022 report by McKinsey, up to 30% of jobs could be automated by 2030, but this will also lead to the creation of new roles that don’t exist today (McKinsey Global Institute, 2022). For teens, this means the future job market will be dynamic, with a mix of challenges and exciting opportunities.
Some jobs will inevitably be displaced by AI, particularly those involving repetitive or manual tasks. For example, self-checkout machines are already reducing the need for cashiers, and autonomous vehicles could one day replace truck drivers. However, new jobs will emerge in areas like AI development, data science, and AI ethics. The U.S. Bureau of Labor Statistics projects that employment of data scientists will grow by 31% from 2019 to 2029, much faster than the average for all occupations (BLS, 2021). This is just one example of how AI is creating demand for new skills.
But there’s a catch: the transition won’t be seamless. A 2019 survey by the World Economic Forum found that 54% of employees will require significant reskilling by 2022 to keep up with technological changes (WEF, 2019). For teens, this underscores the importance of being adaptable and committed to lifelong learning. The jobs of the future will require not just technical know-how but also creativity, emotional intelligence, and the ability to solve complex problems—skills that AI can’t easily replicate.
So, what kinds of jobs will be in demand? Roles like AI ethicists, who ensure AI systems are fair and unbiased, and data scientists, who analyze large datasets to uncover insights, are already emerging. Robotics engineers will design and maintain automated systems, while AI trainers will teach machines to perform tasks like recognizing speech or understanding emotions. These are just a few examples, but the key takeaway is that the future job market will reward those who can work alongside AI, not against it. Teens who develop a mix of technical and soft skills will be well-positioned to thrive in this new landscape.
Skills for the AI-Driven Future
So, what skills do you need to succeed in a world where AI is everywhere? The good news is that you don’t have to be a coding genius to thrive in the future job market. While technical skills are important, soft skills like creativity, critical thinking, and emotional intelligence will be just as valuable. Let’s break it down.
Understanding the basics of AI, machine learning, and data analysis will be crucial in many fields. Learning to code is a great starting point—languages like Python are widely used in AI development and are beginner-friendly. Platforms like Codecademy, Coursera, and Khan Academy offer free or low-cost courses to help you get started. Even if you don’t plan to become a programmer, having a basic understanding of how AI works will give you a competitive edge.
AI is great at handling data and performing repetitive tasks, but it struggles with things like creativity, empathy, and complex decision-making. That’s where humans excel. Jobs that require artistic creativity, strategic thinking, or emotional intelligence—such as design, marketing, healthcare, and education—will remain in high demand. For example, while AI can generate music or art, it can’t replicate the unique perspective and emotional depth that a human artist brings to their work.
Additionally, ethical reasoning will become increasingly important as AI raises complex moral questions. Who is responsible if an AI system makes a mistake? How do we ensure that AI doesn’t reinforce societal biases? Teens who can think critically about these issues will be valuable assets in any organization. By developing this blend of technical and soft skills, you’ll be well-prepared for the AI-driven future. AI is a tool—it’s up to humans to decide how to use it effectively and responsibly.
AI’s rapid growth brings with it a host of ethical challenges that society must address. As future leaders, innovators, and workers, teens need to be aware of these issues and think critically about how to navigate them.
One of the biggest concerns is that AI systems can perpetuate or even amplify existing biases. For example, if an AI is trained on data that reflects societal inequalities, it may make biased decisions. A 2018 study by MIT researchers found that facial recognition systems had higher error rates for women and people of color, highlighting the need for more diverse and representative data (Buolamwini & Gebru, 2018). Teens should advocate for fairness and transparency in AI development, ensuring that technology benefits everyone, not just a select few.
While AI will create new jobs, it will also displace workers in certain industries. This could lead to economic inequality if not managed properly. Policymakers, educators, and businesses need to work together to provide retraining programs and support for those affected. For teens, this means being proactive about learning new skills and staying adaptable in a changing job market.
AI systems often rely on vast amounts of data, raising questions about privacy and data ownership. Who has access to your personal information, and how is it being used? The European Union’s General Data Protection Regulation (GDPR) is one attempt to protect user privacy, but global standards are still evolving. Teens should be mindful of their digital footprint and advocate for stronger privacy protections.
Not everyone has equal access to AI technology, which could widen the gap between those who can afford it and those who can’t. This digital divide could exacerbate existing inequalities in education, healthcare, and job opportunities. Teens can play a role in promoting digital inclusion by supporting initiatives that provide technology access to underserved communities. These ethical considerations are not just theoretical—they have real-world implications for how AI will shape society.
Preparing for the Future: A Call to Action
The future of work with AI is not something to fear—it’s something to prepare for. As a teenager, you have the advantage of time and curiosity on your side. Start by learning about AI through online courses or school clubs—websites like Coursera, edX, and Khan Academy offer free introductions to AI and machine learning. Focus on developing both technical skills (like coding) and soft skills (like creativity and emotional intelligence) to stay versatile in any career.
Stay informed by following AI news and trends through blogs, podcasts, or YouTube channels. Understanding how AI is evolving will help you anticipate future opportunities. Talk with friends, teachers, or mentors about the ethical implications of AI—being part of the conversation will help you think critically about technology’s role in society. Try building simple AI projects using platforms like TensorFlow or Scratch—hands-on experience will deepen your understanding and spark creativity.
By taking these steps, you’ll be better equipped to navigate the future job market and contribute to shaping a world where AI works for everyone. AI is a tool—how we use it will determine its impact. As the next generation, you have the power to ensure that AI is used responsibly and creatively to solve the world’s biggest challenges.
Key Takeaways
AI is transforming industries like healthcare, finance, and education, creating new opportunities but also displacing some jobs.
The future job market will require a mix of technical skills (e.g., coding, data analysis) and soft skills (e.g., creativity, emotional intelligence).
Ethical considerations, such as bias, privacy, and job displacement, are critical in ensuring AI benefits society as a whole.
Teens can prepare for the future by learning about AI, developing diverse skills, staying informed, and engaging in ethical discussions.
AI is a tool that will shape the future of work—how we use it depends on us.
References
Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency. Retrieved from http://proceedings.mlr.press/v81/buolamwini18a.html
Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115-118. Retrieved from https://www.nature.com/articles/nature21056
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