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Unregulated AI and capitalism may worsen inequality
🗞️ The Tech Issue | August 2, 2023
Qamar Zia
August 02, 2023
☕️ Greetings. It's Wednesday, August 2. I've got some awesome updates to share with you today. Brace yourself for the coolest AI trends, valuable insights, resources, and mind-blowing cutting-edge tools. Get ready to be amazed! First time reading? join here! If you like my newsletter, please share it with your team. It will help me immensely.
Hollywood writers and actors are striking due to concerns about AI-driven automation replacing human creative work, leading to job loss and economic inequality. Economist Joseph E. Stiglitz emphasizes that unregulated AI and capitalism can worsen inequality. While AI may create some new jobs, it's unlikely to compensate fully for the jobs lost. The rise of AI-generated content could reshape job skills and decrease demand for certain roles. Stiglitz suggests government intervention, active labor market policies, and shorter workweeks as potential solutions to mitigate AI's impact on inequality. He expresses pessimism about addressing inequality through policy and emphasizes the need for careful consideration of historical parallels.
The digital era has sparked interest in human-like relationships with robots, blurring the lines between human and AI connections. Emotional attachments form due to predictability, but simulated emotional bonds raise questions about love. Companion robots offer support, yet neglecting human bonds and manipulation are risks. While technology matters, genuine human connections remain unmatched. Balancing innovation and ethics is crucial for a future valuing tech progress and human relationships.
🗞️ Today’s Highlights:
EXECUTIVE — How generative AI impacts your digital transformation priorities
IDEAS & QUESTIONS — Google is training robots the way it trains AI chatbots
LEARNING — Top 10 Machine Learning Projects For Beginners in 2023
AI TOOLS — Postwise AI: Craft engaging posts with AI, schedule effortlessly, and watch your followers grow
INDUSTRY & FUNCTIONS — How AI is transforming MarTech
WORK — How AI-powered software development may affect labor markets
🗞️ EXECUTIVE
Heading into 2024, CIOs must reshape their digital agenda to embrace generative AI while managing risks. They should define a strategy, prepare data for LLMs, improve customer support, establish governance, and prioritize ethical decision-making. These steps will unlock the potential of AI while safeguarding sensitive information and ensuring responsible use.
AI is revolutionizing business sectors like customer service, talent management, and application modernization. IBM's IBV suggests AI can boost customer experience by 70% and productivity by 40%. Data quality and trust are vital. Data lakehouses support AI-powered knowledge systems, ensuring secure and efficient data usage. Proactive bias detection is essential for reliable AI responses.
🗞️ IDEAS & QUESTIONS
Google has introduced its AI learning model called Robotic Transformer (RT-2), an updated version of the vision-language-action (VLA) model, aimed at making robots smarter. RT-2 enables robots to better understand visual and language patterns, interpret instructions, and infer the most suitable objects for a given task. The model was tested successfully with a robotic arm in a kitchen office setting, where it was able to identify an improvised hammer (a rock) and choose a drink for an exhausted person (a Red Bull). The robot also demonstrated its ability to move a Coke can to a picture of Taylor Swift, showcasing its understanding of different languages. RT-2 is trained on web and robotics data, combining Google's Bard language model with robotic information. It represents a significant improvement over traditional robot training methods, which required laborious manual programming of directions. While there are still some imperfections, the development of smarter robots continues to advance, promising potential applications in real-life environments in the near future.
Image source: Google
This article from GovTech.com discusses the challenges legal professionals can face with generative AI, as some courts have resisted its use, while others view it as a time-saving tool. The technology can be helpful for legal research and drafting documents, but relying too heavily on it can lead to false information being generated. Concerns also arise with the emergence of deepfaked evidence, which poses difficulties in detecting manipulated media. Some courts have implemented rules around AI use, requiring validation through traditional methods. Specialized generative AI trained on legal texts shows promise, but caution is still necessary. To mitigate deepfake concerns, disclosure of AI use in evidence submissions and digital watermarking are potential solutions.
🗞️ LEARNING
Generative AI Studio is a Google Cloud tool for quick prototyping and testing of generative AI models. It allows you to experiment with sample prompts, create custom prompts, and adapt foundation models to suit your application. The tool facilitates tasks such as testing models, designing prompts, tuning foundation models, and converting between speech and text.
Video source: Google
The article discusses the top 10 machine learning projects for beginners to learn and develop their skills. It covers projects like movie recommendations, TensorFlow, sales forecasting with Walmart data, stock price predictions, human activity recognition with smartphones, wine quality predictions, breast cancer prediction, iris classification, sorting specific tweets on Twitter, and turning handwritten documents into digitized versions.
The article also highlights the importance of machine learning in various applications, and it encourages professionals to pursue careers in machine learning by taking relevant courses and certifications. It provides information about different programs and courses available for learning AI and machine learning.
The FAQs section answers common questions related to starting machine learning projects, the difference between AI and machine learning, learning AI and ML for free, suitable languages for machine learning, finding machine learning projects, and the key steps in a machine learning project.
🗞️ AI TOOLS
Octocom: The best AI chatbot for your Ecommerce store.
Postwise AI: Craft engaging posts with AI, schedule effortlessly, and watch your followers grow
Photo AI: Create stunning selfies with AI - no camera
Aragon AI: Transform your Selfies into AI-Generated Headshots
Speedwrite: The secret weapon for awesome text. Unique writing, every time.
120 AI Tools: Productivity, Writing, Video, Marketing, Chatbots, Design
Source: Reddit - Posted by u/jpc4stro.
Disclaimer: 1) The tool descriptions may include messaging from each tool site. 2) Please thoroughly read the site details before using and/or acquiring any of the tools listed above.
🗞️ INDUSTRY & FUNCTION
Artificial Intelligence (AI) is reshaping marketing technology, offering benefits like accurate consumer behavior prediction and process automation. Natural Language Processing (NLP) aids customer communication, while predictive analytics enhances audience segmentation. Augmented analytics provides meaningful insights, and computer vision enables precise contextual ads. AI-driven content creation, sentiment analysis, and voice AI are transforming marketing. Contextual targeting and image recognition refine advertising, while AI assists in multi-channel attribution. Implementing AI requires evaluating needs and data readiness, with AI bringing innovation and solutions to various marketing challenges.
Generative AI and Large Language Models (LLMs) like GPT-3.5 are impactful but require adaptation due to challenges like workforce changes, expertise gaps, and ethics. Their impact includes augmenting the workforce, industry-specific adoption, and enhancing products. A strategic approach involves short-term efficiency, medium-term innovation, and long-term transformation using applications like employee knowledge bases, virtual assistants, and data analytics. Gen AI startups attract funding, with successful areas being copywriting and coding. Margins improve as efficiency grows, offering significant growth potential.
🗞️ WORK
This article published by Brookings Institution discusses how generative AI tools are being used in software development and their impact on productivity and labor demand. It presents experimental findings showing potential productivity gains, discusses implications for various occupations, and suggests policies for supporting workforce adaptation and responsible AI integration. The research highlights that while generative AI can enhance productivity, it may also lead to new tasks and specialties, potentially increasing demand for workers. Policy recommendations include education, upskilling, and fostering AI development to complement, not replace human labor.
The rapid integration of AI technology into various industries is causing shifts in the job market. Customer-facing and low-income roles are expected to decline due to automation, with around 10 million occupational shifts predicted by 2030. Sectors like e-commerce, office admin, food service, and production work will be most affected. Meanwhile, industries like healthcare, high-paying jobs, management, transportation, and STEM fields are projected to thrive, with the health care sector expected to add 3.5 million jobs. While stable, even high-paying roles will experience changes in daily tasks due to AI's influence.
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