WORKFORCE

Silicon Valley is still losing the AI jobs debate

Despite AI leaders preaching about how AI can transform the workforce for the better, the public is not convinced.

A study published Thursday by Pew Research Center found that people broadly believe that AI will diminish job opportunities, rather than create them. The report, which included more than 42,000 people across 36 countries, finds that 46% of survey respondents believe that AI will lead to fewer jobs, while only 9% said it would lead to more. Around 13% reported that the tech would have a minimal impact on jobs, while 25% reported they weren't sure. 

Although responses differed by country, Australia, South Korea and the US were the least confident overall about AI's economic and labor impacts. Around 76% of both Australian and South Korean respondents reported that AI will lead to fewer jobs, while 71% of US respondents reported the same. 

Several respondents said AI would cause the middle class to dwindle by widening the gap between the rich and the poor, with 46% of respondents in the US sharing this view. Young people are also more likely than those 50 and older to say that AI will fuel the gap between the rich and poor, with 56% of young people in the US, compared to 38% of those 50 and older, reporting this belief. 

While this study highlights how widespread public concern is about AI-related job losses, this narrative isn't new. AI is facing a PR crisis outside the Silicon Valley bubble, with a March report from Quinnipiac University finding that 55% of Americans felt AI would do more harm than good, and 70% believed AI will reduce job opportunities. 

These fears may not be unfounded, and job losses appear to be hitting Silicon Valley first. Tech employers filed layoff notices for more than 14,500 Bay Area employees between June 2025 and June 2026, according to analysis published by Bloomberg on Thursday. But keep in mind that the San Francisco Bay Area employs about 375,000 tech workers overall, down about 7% since 2024.

There have been a number of conflicting narratives about how AI will impact the workforce, with some claiming that AI will create entirely new jobs that force companies to rehire laid-off workers, while some positions are already ripe for automation. But two things are already starkly true: First, companies can, will, and have used AI as a scapegoat to cut labor costs. Second, the public still largely distrusts the tech. This creates a dilemma for AI leaders: While enterprises are largely their cash cow, the frontier labs still need public buy-in to achieve their broader scaling and adoption goals. While the reality of how many jobs AI will create versus how many it will destroy remains unclear, the AI industry needs to do a much better job of articulating the opportunities for growth, because it's still losing the narrative.

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PRODUCTS

How Slack got new superpowers for AI

Slack has already all but replaced email in many organizations, and now it's going after your most important business apps. 

At Dreamforce 2026 this week in San Francisco, Salesforce showed off upgrades to Slack that make it clear the company is doubling down on one of the world’s most used business apps. Foremost among the upgrades is Slackforce, which lets you do nearly everything in Salesforce directly in Slack. You can simply query it like a chatbot. That includes a new feature called Slackforce Surface, where you can describe what you need and Slack will build a live interactive interface that you and your teammates can use to track data, view forecasts, monitor pipelines, and manage other business processes. 

But Salesforce also announced a slew of other Slack upgrades:

• Slack Code: Lets teams code together directly in a Slack code channel using agents from OpenAI, Anthropic, GitHub, Cognition, and Vercel

• Big Mode: This full-screen Slackbot view offers an AI workspace for more intensive tasks like research, writing, and creating files

• Slackbot in Salesforce Lightning: This brings Slack's AI agent into Salesforce to take advantage of all of the expanded AI capabilities of Slackbot for those who still want to work in the Salesforce interface

• Two-way Slackbot voice: You'll be able to speak to Slackbot in natural language, similar to ChatGPT Voice and Siri AI when this feature launches later in 2026

• Slackbot video generation: Will let you take a demo, product update, campaign brief, or other asset and turn it into a video clip, when it's released later this fall

A few months ago, Salesforce co-founder Parker Harris said, "You may never log in to Salesforce again," referring to the company making Salesforce more readily available in the AI interfaces users prefer. That includes the new AIforce, Claudeforce, and Headless 360 moves we talked about yesterday, but it also includes Slackforce and these broader Slack upgrades.

It makes sense for Salesforce to invest heavily in expanding Slack's footprint and upgrading its AI capabilities. It remains one of the world's most popular workplace apps, and unlike many of the other widely used business apps, users tend to like it. But moving a system of record (SoR) like Salesforce into Slack and upgrading Slack's AI capabilities to interrogate systems with queries and tasks points to a bigger shift. SaaS and software companies are no longer trying to excel with the best apps and interfaces, but are creating safe, secure, low-friction ways for people and organizations to get more out of the data, intelligence, and best practices embedded in their company's most valuable assets (and often difficult to surface). From an employee perspective, using the Slack app they already use every day as an on-ramp to safe AI could be a welcome development compared to context-switching to ChatGPT, Claude, Copilot, or other AI apps. The implementation details will matter a lot, of course. But if Slackbot can do model routing to save token costs and play to the strengths of different models and evolve into one of the most capable agent harnesses on the market, it could be a win-win.

Disclaimer: Jason Hiner's travel to Dreamforce 2026 was paid for by Salesforce. The Deep View's coverage is editorially independent from the companies we cover.

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CONSUMER

Why Apple Watch S12 is a model for stealth AI

In a world filled with so much AI-washing, Apple has taken a refreshing approach with its Apple Watch Series 12, letting the technology work quietly in the background to enhance the user experience rather than plastering it across the product's marketing material. 

Last Wednesday, Apple unveiled the Apple Watch Series 12 and Apple Watch Ultra 4. Both watches run on Apple's new S11 chip, which powers many new AI features and algorithms, as well as the efficiency gains needed to run them. The S11 enables flashy AI features like Siri Recap and Live Rewind, and it drives new health features that give users deeper insight into their bodies. 

The all-new Health Sensing System, enabled by both the chip and new optical and electrical heart sensors, can now provide frequent heart rate variability (HRV) readings and heart rate tracking. This is important as it gives users more detailed insight into their health, including stress and recovery. For comparison, HRV is now measured every 5 minutes, whereas previously it was measured roughly every 2 to 4 hours, and heart rate readings occur every 5 seconds, whereas previously they were attempted every 5 minutes. 

The unsung heroes are the machine learning models working in the background to help make sense of all this data, which, though Apple is smart not to market it as AI, are still examples of AI doing important work. Other companies should take note of the subdued approach. 

More examples of this include the redesigned pedometer model, which is powered by new machine learning algorithms to provide more accurate step tracking, or the new Readiness score, which provides a single 0-10 score with a designation that reads "Recover, Pace Yourself, Ready, or Go For It." 

I'm personally super excited to try this feature, but I haven't been able to because you need 7 consecutive days of 4+ hours of sleep, which I haven't yet gotten because I'm a journalist and it's Techtember. Later in the year, users will also be able to see a conversational Readiness summary of their metrics. 

Of course, the new and improved Siri AI on watchOS 27 is a signature feature, and it has been a delight using it on the go from my wrist. And we have to mention the new Audio Intelligence features, Live Rewind and Siri Recap, which we've already covered in depth and which will be coming in beta in a couple of months.

A fun feature worth trying now is the improved Shazam, which is meant to let you automatically see the names of songs playing around you, ambiently, without having to tap a widget. This does not mean the widget automatically populates, as the Now Playing feature on Google Pixel phones does. Rather, you have to activate the Smart Stack by tapping your thumb and index finger or by scrolling the Digital Crown upward. Still, Shazam works as described, and it's pretty handy. However, it wasn't quite enough to satisfy my appetite for the rest of the AI features coming later this year, which I'm eager to test and report back.

As someone who tried AI fitness coaches as early as 2023 and has seen these summaries typically promoted as AI features, I'm pleased that Apple is not marketing the Apple Watch features as part of Apple Intelligence, but is instead presenting them as useful updates. There are also many more features that I wasn't able to cover in this article, given its length, such as the redesigned Health app and the Health Age feature coming in late 2026. Despite the added features, battery life remains unaffected, thanks to the new S11 chipset. Apple still claims up to 24 hours of battery life, and I found that to be accurate. Charging is super efficient, going from a dead battery to nearly 30% in just ten minutes. When looking for an ideal AI wearable, the things you always want to improve are the data you receive, how quickly you can make sense of it, and battery life. By optimizing its own silicon and the latest machine learning models, Apple has been able to deliver on all three so far. The new Audio Intelligence features could challenge that, so we can't wait to start testing at the end of the year.

LINKS

• Andrew Ng calls AI extinction discussions "science fiction" 

• OpenAI reportedly expects to solve another Millennium Prize problem

• Lucid, Bolt sign agreement to deploy 25,000 robotaxis in Europe

• Manus eyes $500 billion funding round at $4 billion valuation

• World models firm Emulate in talks for $700 million, $3.7 billion valuation

• Tech giants launch AI Energy Management Alliance for data center power

• Perplexity Computer: Launches ‘Effort’ controls to optimize models for your tasks to control costs, speed, and frontier intelligence

• Astra for Law: OpenAI's frontier model GPT-6 is now available specifically for legal use cases

• Arrow 2: The latest model from Quiver for generating precise, editable vector graphics.

• Higgsfield API: Includes more than 50 frontier models in one API, with up to a 50% discount on three models of your choice. 

• Claude Code: Now in a project, users can describe what needs to get done and Claude manages the work.

• Hewlett Packard Enterprise: AI/ML Engineer - Agentic

• Bland: Machine Learning Researcher, Multimodal LLMs

• Adobe: Senior / Prompt Engineer (AI/ML), Brand Concierge

• Stanford University: AI Engineer

GAMES

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