Edumorfosis.Work

La Inteligencia Artificial (IA) nos brinda la oportunidad de decidir en qué merece la pena gastar nuestra vida, algo que nunca habíamos podido elegir. Es una oferta irrechazable pero no exenta de peligros. Yo tengo jardín y le puedo preguntar a Picture This que me diga qué enfermedad tiene una planta y cómo tratarla. Es decir, que me provea conocimiento que no tengo y que anteriormente debía consultar a mi jardinero. El jardinero, en lugar de dedicar su tiempo a saberlo todo sobre cada planta, podrá ofrecerme conocimiento sobre planificación, producción, diseño, comercialización, etc. apoyado en otra IA. El límite será nuestra imaginación, que nunca fue una capacidad muy valorada…

El AI-Enabled ICT Workforce Consortium, liderado por Cisco, junto con Accenture, Eightfold, Google, IBM, Indeed, Intel, Microsoft, SAP y otras empresas asesoras, ha publicado su informe inaugural: “La oportunidad transformadora de la IA en los empleos de TIC”.

Este análisis integral proporciona una visión sin precedentes de los efectos de la inteligencia artificial en casi 50 puestos de trabajo principales de las tecnologías de la información y la comunicación (TIC) , y ofrece recomendaciones de capacitación para habilitar una fuerza laboral impulsada por la IA.

Reid Hoffman, pionero de Silicon Valley, explica por qué deberíamos considerar la IA generativa como una “máquina de vapor de la mente” que promete alterar profundamente nuestra vida profesional y personal.

In the beginning of the universe, all was darkness — until the first organisms developed sight, which ushered in an explosion of life, learning and progress. AI pioneer Fei-Fei Li says a similar moment is about to happen for computers and robots. She shows how machines are gaining "spatial intelligence" — the ability to process visual data, make predictions and act upon those predictions — and shares how this could enable AI to interact with humans in the real world.

Artificial Intelligence (AI) has revolutionized everything from customer service to content creation, giving us tools like ChatGPT and Google Gemini that can generate human-like text or images with remarkable accuracy. But there’s a growing problem on the horizon that could undermine all of AI’s achievements—a phenomenon known as "model collapse."

Model collapse, recently detailed in a Nature article by a team of researchers, is what happens when AI models are trained on data that includes content generated by earlier versions of themselves. Over time, this recursive process causes the models to drift further away from the original data distribution, losing the ability to accurately represent the world as it really is. Instead of improving, the AI starts to make mistakes that compound over generations, leading to outputs that are increasingly distorted and unreliable.

La adopción de la inteligencia artificial en Sudáfrica está en aumento y, mientras promete revolucionar aspectos de la vida diaria, también plantea retos.

Artificial Intelligence has the potential to reshape our economies, labor markets, societies, and politics. But despite the rosy forecasts of an AI-driven boom, history shows that technological advances rarely lead to immediate improvements in living standards and often lead to profound disruption.

Just a few years back, if you had been told that by 2024, you would be able to have a conversation with a computer that would seem almost completely human, would you have believed it?

So what do you think AI will be capable of in ten, twenty or even fifty years’ time?

Of course, it’s impossible to predict for sure – but it seems a fairly safe bet that many things that seem entirely impossible today will be a part of everyday life.

By now, it’s clear that AI is the great breakthrough technology of our times. And as with other breakthrough technologies – fire, steam power, electricity, computing – now it exists, it is only going to continue to evolve and become more capable.

However, one unique feature of AI is its ability to improve itself. As AI helps create more advanced AI, I believe progress will accelerate in ways that we haven’t previously seen.

• Technology, including artificial intelligence (AI), must be deflationary to have a macroeconomic impact. It can reduce costs and prices and boost real incomes and demand, thereby creating new jobs and offsetting automation-driven losses.
• Predictions of technological unemployment have repeatedly proven false, as macroeconomic job creation in new sectors offsets microeconomic disruptions.
• AI is likely to increase productivity and wealth, with new jobs emerging; the focus should be on managing sector-specific disruptions, not fearing labour market dystopia.

La Inteligencia Artificial Generativa (IAG) podría transformar significativamente los empleos e impulsar la productividad en América Latina y el Caribe, pero las brechas existentes en la infraestructura digital podrían obstaculizar sus beneficios potenciales, según un nuevo estudio de la Organización Internacional del Trabajo (OIT) y el Banco Mundial.

La investigación, La IA generativa y los empleos en América Latina y el Caribe: ¿La brecha digital es un amortiguador o un cuello de botella?, concluye que entre el 26% y el 38% de los empleos de la región podrían verse influidos por la GenAI. Sin embargo, es más probable que la tecnología aumente y transforme los puestos de trabajo en lugar de automatizarlos por completo. En concreto, entre el 8% y el 14% de los empleos podrían ver mejorada su productividad gracias a la GenAI, mientras que sólo entre el 2% y el 5% corren el riesgo de automatización total.

The data is in: 2024 is the year AI at work gets real. Use of generative AI has nearly doubled in the last six months, with 75% of global knowledge workers using it. And employees, struggling under the pace and volume of work, are bringing their own AI to work. While leaders agree AI is a business imperative, many believe their organization lacks a plan and vision to go from individual impact to applying AI to drive the bottom line. The pressure to show immediate ROI is making leaders inert, even in the face of AI inevitability.

We’ve come to the hard part of any tech disruption: moving past experimentation to business transformation. Just as we saw with the advent of the internet or the PC, business transformation comes with broad adoption. Organizations that apply AI to drive growth, manage costs, and deliver greater value to customers will pull ahead.

At the same time, the labor market is set to shift again—with AI playing a major role. Despite fears of job loss, leaders report a talent shortage for key roles. And as more employees eye a career move, managers say AI aptitude could rival experience. For many employees, AI will raise the bar but break the career ceiling.

In our fourth annual Work Trend Index, out today, we partnered with LinkedIn for the first time on a joint report so we could provide a comprehensive view of how AI is not only reshaping work, but the labor market more broadly. We surveyed 31,000 people across 31 countries, identified labor and hiring trends from LinkedIn, analyzed trillions of Microsoft 365 productivity signals and conducted research with Fortune 500 customers. The data points to insights every leader and professional needs to know — and actions they can take — when it comes to AI’s implications for work.

Imagine walking into your office and noticing your colleague Sarah effortlessly breezing through her tasks with uncanny efficiency. Her secret? It might just be AI. A groundbreaking global survey by the Workforce Lab at Slack has unveiled a fascinating trend: the rise of the secret AI user in the workplace.

While executives are keen to integrate AI into their operations, with 96% feeling an urgent need to do so, many employees are quietly experimenting with these tools on their own. The number of leaders aiming to implement AI "in the next 18 months" has skyrocketed by 700% since September 2023. Yet, paradoxically, more than two-thirds of desk workers have yet to officially dip their toes into the AI pool at work.

Large language models, comprising billions of parameters and pre-trained on extensive web-scale corpora, have been claimed to acquire certain capabilities without having been specifically trained on them. These capabilities, referred to as “emergent abilities,” have been a driving force in discussions regarding the potentials and risks of language models. A key challenge in evaluating emergent abilities is that they are confounded by model competencies that arise through alternative prompting techniques, including in-context learning, which is the ability of models to complete a task based on a few examples. We present a novel theory that explains emergent abilities, taking into account their potential confounding factors, and rigorously substantiate this theory through over 1000 experiments. Our findings suggest that purported emergent abilities are not truly emergent, but result from a combination of in-context learning, model memory, and linguistic knowledge. Our work is a foundational step in explaining language model performance, providing a template for their efficient use and clarifying the paradox of their ability to excel in some instances while faltering in others. Thus, we demonstrate that their capabilities should not be overestimated.

Si hasta ahora hemos disfrutado de la Era de la "IA Conversacional" , a partir de Strawberry conoceremos el potencial de la "IA Razonadora", antes de poder entrar en la Era de la "IA Autónoma": agentes inteligentes dotados de IA que serán capaces de realizar las tareas precisas para conseguir el objetivo del usuario interactuando con todo tipo de sistemas.

Según informes recientes de The Information, el lanzamiento de Strawberry podría producirse en las próximas dos semanas, adelantándose a las expectativas iniciales que lo situaban para el otoño. Lo que distingue a Strawberry de sus predecesores es su capacidad para "pensar" antes de responder, un proceso que puede tomar entre 10 y 20 segundos.

The AI revolution that we’re currently living through is a direct result of the explosion in the amount of data that’s available to be mined and analyzed for insights.

However, collecting data from the real world can be challenging. Storing and working with personal data creates privacy and security challenges, and other types of data can be expensive or even dangerous.

So why not generate artificial data that’s close enough to real-world data that it can be used for many of the same purposes at a fraction of the cost in terms of time, money and risk? That’s the promise of synthetic data - another field where Generative AI is quickly becoming a valuable tool.

Hace unos años, si alguien me hubiera dicho que estaría creando parques temáticos virtuales donde personas de diferentes países podrían caminar juntas, reírse, aprender y divertirse, probablemente habría pensado que estaban viendo demasiadas películas de ciencia ficción. Pero aquí estoy, como diseñadora gráfica, viviendo en un mundo donde eso es posible, y todo gracias a las nuevas tecnologías como la realidad virtual (VR) y la inteligencia artificial (IA).

Sé lo que estás pensando: “Pero, ¿la IA no va a atrofia nuestro pensamiento creativo?”. Pues, déjame decirte que, en mi experiencia, ¡es todo lo contrario! La IA no solo potencia la creatividad, sino que también te da la libertad de enfocarte en lo que realmente importa: ¡dar rienda suelta a tu imaginación!

The baseline forecast is for the world economy to continue growing at 3.2% during 2024 and 2025, at the same pace as in 2023. A slight acceleration for advanced economies—where growth is expected to rise from 1.6% in 2023 to 1.7% in 2024 and 1.8% in 2025—will be offset by a modest slowdown in emerging market and developing economies from 4.3% in 2023 to 4.2% in both 2024 and 2025. The forecast for global growth five years from now—at 3.1%—is at its lowest in decades. Global inflation is forecast to decline steadily, from 6.8% in 2023 to 5.9% in 2024 and 4.5% in 2025, with advanced economies returning to their inflation targets sooner than emerging market and developing economies. Core inflation is generally projected to decline more gradually.

The risks posed by Artificial Intelligence (AI) are of considerable concern to academics, auditors, policymakers, AI companies, and the public. However, a lack of shared understanding of AI risks can impede our ability to comprehensively discuss, research, and react to them. This paper addresses this gap by creating an AI Risk Repository to serve as a common frame of reference.

This comprises a living database of 777 risks extracted from 43 taxonomies, which can be filtered based on two overarching taxonomies and easily accessed, modified, and updated via our website and online spreadsheets. We construct our Repository with a systematic review of taxonomies and other structured classifications of AI risk followed by an expert consultation.

We develop our taxonomies of AI risk using a best-fit framework synthesis. Our high-level Causal Taxonomy of AI Risks classifies each risk by its causal factors (1) Entity: Human, AI; (2) Intentionality: Intentional, Unintentional; and (3) Timing: Pre-deployment; Post-deployment. Our mid-level Domain Taxonomy
of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6)
Socioeconomic & environmental, and (7) AI system safety, failures, & limitations. These are further divided into 23 subdomains.

The AI Risk Repository is, to our knowledge, the first attempt to rigorously curate, analyze, and extract AI risk frameworks into a publicly accessible, comprehensive, extensible, and categorized risk database. This creates a foundation for a more coordinated, coherent, and complete approach to defining, auditing, and managing the risks posed by AI systems.

Roberto Romero, experto en nuevas tecnologías, comparte su experiencia sobre cómo innovar con inteligencia artificial. Destaca la importancia de la educación y la adaptación de herramientas tecnológicas en el ámbito creativo. La IA puede democratizar la creación de contenido, pero su éxito depende de la comprensión y habilidades de los usuarios.

• 93% of IT and business decision-makers Be the AI orchestrator: Organizations are eager to adopt AI for competitive advantage and must carefully consider the complexity and interdependencies of AI within the organization to be successful. 
• AI is a top priority and 43% believe it will be a “game changer,” transforming how they run their business: Half of the ITBDMs say they need to invest in Generative AI (GenAI) capabilities to keep up with their competition. 
• Infrastructure decisions must support the organizational AI strategy: Hybrid cloud deployment models are expected to be the most prominent, but beyond cloud investments, the anticipated spending growth in edge computing will help support real-time analytics and insights. 
• People issues are holding everyone back: Overcoming  concerns that employees’ jobs will be threatened is a key challenge to successful AI adoption. Employees need the relevant skills and a “data culture” for AI to succeed in the enterprise. 

En un mercado laboral dinámico y en constante evolución, atraer y retener a la Generación Z representa un desafío significativo para las organizaciones. Este grupo, nacido entre 1997 y 2012, no solo busca compensación económica, sino también un ambiente laboral que valore su bienestar emocional y personal. El concepto de “salario emocional” se presenta como una solución eficaz para cumplir con estas expectativas.

Thanks to AI, work will look very different in the near future than it does today. According to the World Economic Forum, 85 million jobs will be impacted by AI by 2030, and millions of new jobs will be created that don’t yet exist.

In a world where the pace of change is accelerating dramatically, it will be our skills -rather than our education, work history or past achievements – that define our value.

In practical terms, employers will be less concerned about what we know or have achieved in the past and more interested in how we can apply knowledge and abilities to solving modern business challenges.

Are you using or thinking about using AI to help you at work? You’re not alone. This year’s annual Work Trend Index (WTI) from Microsoft and LinkedIn found that 84% of Hispanic and Latinx knowledge workers use generative AI in the workplace. This type of artificial intelligence can create new content, such as text or images, based on data it has been trained on, and can be applied to diverse fields of work. Furthermore, 72% of Hispanic and Latinx AI users are using their own AI tools and applications at work rather than relying solely on those provided by their employers. This is consistent with the fact that our Hispanic and Latinx community has traditionally been quick to adopt new technologies with large shares of smartphone ownership and social media use.