Akingate Consultancy

Is AI really coming for our jobs and wages? Past predictions of a ‘robot apocalypse’ offer some clues

Akingate — Tue, 11 Nov 2025 20:02:22 +0000

The robots were taking our jobs – or so we were told over a decade ago. The same warnings are regularly heard today about the likely impact of artificial intelligence (AI).

Tech breakthroughs have long stirred fears of workplaces being wiped out by automation, with generative AI platforms such as ChatGPT inspiring the latest round of occupational angst.

We often see this dread of AI replacing our livelihoods in news articles reporting on new worker survey findings, or in online forums talking of AI “job massacres”.

A similar gloom pervaded earlier research speculating about the future impact of automation and an impending robot apocalypse.

At Oxford University, researchers Carl Benedikt Frey and Michael Osborne warned in 2013 that 47% of US jobs were at high risk of automation “perhaps in a decade or two”.

Soon after, the New Zealand Institute of Economic Research estimated some 50% of New Zealand jobs might also be vulnerable.

The media amplified such warnings with alarming headlines such as “You Will Lose Your Job to a Robot – and Sooner Than You Think”.

In 2017, Nobel Prize winner Daron Acemoglu and Pascual Restrepo provided the first concrete evidence that robots had begun displacing jobs and lowering wages in the US economy.

Their findings sparked a global wave of research, as hundreds of scholars began analysing various datasets in search of further proof.

The robo-revolution that wasn’t

More than a decade on from these forecasts first appearing, was the gloom ever justified? Did this threat to our jobs and wages really play out?

To answer these questions, my colleagues and I carried out a meta-analysis synthesising the results of dozens of academic papers published since Acemoglu and Restrepo’s landmark 2017 study.

Rather than relying on a single dataset, country or time period, we reviewed 52 studies from around the world, covering a total of 2,586 individual estimates of how robots and automation affect wages.

Across the 52 studies reviewed, we found no strong evidence that robots have a consistent impact on wages – either positive or negative.

Some studies reported wage declines, others found increases, but on average, the effect was close to zero. In fact, the estimated overall impact was so small that it fell below even the minimal threshold for economic significance.

While robots might affect wages in specific industries and countries, or among certain groups of workers, we found little global evidence to support the idea that automation is consistently driving wages up or down.

An earlier University of Canterbury-led meta-analysis found similar results when examining the impact of robots on employment.

While those initial findings by Acemoglu and Restrepo showed robots reduced employment, much of the research since has shown no overall negative effect.

Two other meta-analyses, led by researchers in Italy and Germany, also turned up scant consistent evidence for widespread, robot-driven cuts to jobs and wages.

Focus on opportunity, not anxiety

Despite these findings, we still can’t say there have been no losers – or winners – amid the rise of automation.

Indeed, some job types, such as those performing routine cognitive or physical tasks, have diminished in importance because of robots, while others, such as those requiring creativity, have become increasingly vital.

Our research suggests that upskilling and learning how to collaborate effectively with robots – and AI – is the right strategy for staying competitive in today’s labour markets.

Entrepreneurs and managers should also focus on adapting to and capitalising on the new opportunities that automation creates.

After all, technology advances one company death at a time.

Finally, for policymakers, our research calls for a shift away from panic-driven regulation aimed at slowing automation, and toward supporting workers in gaining those human skills that automation makes more valuable.

The author acknowledges the contributions of his co-researchers Bob Reed and Thomas Logchies from the University of Canterbury.

Author: Tom Coupe, Associate Professor of Economics, University of Canterbury

This article is republished from The Conversation under a Creative Commons license.

ChatGPT-5: The Next-Level AI Revolution for Smarter Conversations in 2025

Akingate — Fri, 08 Aug 2025 14:55:53 +0000

Reading time: 8–10 minutes

ChatGPT-5 brings multimodal understanding and sharper reasoning to everyday workflows.

What is ChatGPT-5?

If you thought ChatGPT‑4 was impressive, buckle up — ChatGPT‑5 levels up everything from comprehension to creativity. Built on next‑gen architecture, it’s designed to understand context more deeply, reason through complex prompts, and interact in ways that feel startlingly natural.

Instead of just responding, ChatGPT‑5 can reason, analyze, and create across formats. Whether you’re drafting proposals, explaining data, or producing content, it acts like a creative partner rather than a simple chatbot.

How ChatGPT-5 Differs from GPT-4

Multimodal understanding: Works across text, images, audio, and short video.
Better context retention: Smoother long-form conversations and projects.
Sharper reasoning: More coherent step-by-step breakdowns for complex tasks.
Personalized interactions: Adapts to your tone and preferences.
Reduced hallucinations: Improved factual accuracy and guardrails.

Tip: When you compare GPT-5 vs GPT-4, test identical prompts and evaluate clarity, correctness, and speed.

Key Features That Make ChatGPT-5 a Game-Changer

Multimodal Magic

Upload an image, ask a question about it, get a voice answer, or have GPT‑5 summarize a short clip — all in one session. It turns visuals and audio into actionable insights.

Hyper-Personalization

Prefer concise answers or deep dives? GPT‑5 adapts. Over time, it mirrors your style and context, making collaboration feel effortless.

Advanced Reasoning & Analysis

From untangling RFPs to explaining statistical models in plain English, GPT‑5 handles layered instructions and delivers step‑wise logic.

Collaborative Creativity

Toss in half-baked ideas and get polished outlines, scripts, or product angles. It’s like brainstorming with a tireless, well‑read partner.

Accessibility Upgrades

With stronger multilingual and voice capabilities, GPT‑5 lowers barriers for global teams and learners.

Real-Life Uses of ChatGPT-5

For Businesses

Automate support with natural, friendly replies.
Draft multi-language campaigns and landing copy.
Turn messy notes into action plans and summaries.

For Education

On-demand tutoring with interactive explanations.
Turn complex topics into visuals and analogies.
Generate essay outlines, quiz items, and feedback.

For Creatives

Brainstorm blog topics and video scripts fast.
Storyboards and concept art prompts in minutes.
SEO descriptions and product copy that convert.

Pros of ChatGPT-5

Highly accurate, context-aware responses.
True multimodal workflows (text, image, audio, video).
Personalized outputs aligned to your voice.
Faster processing and response times.

Cons (What to Watch Out For)

Still benefits from clear, specific prompts.
Critical facts may require verification.
Some features could sit behind paywalls.

How to Get the Best Out of ChatGPT-5

Be specific: “Give 5 innovative marketing ideas for a neighborhood bakery in 2025” beats “marketing tips.”
Use follow-ups: Iterate to refine tone, length, or format.
Leverage multimodality: Add images, docs, or audio for richer context.
Set roles: “Act as a senior copywriter / data analyst / tutor” to guide outputs.

Copy-paste prompt: “Act as a product marketer. Turn these feature notes into a 120-word landing page hero with a CTA and 3 bullets. Keep the tone friendly and confident.”

Want to go deeper into prompt engineering? It’ll pay dividends.

The Future Beyond GPT-5

With ChatGPT‑5, AI shifts from background tool to collaborative teammate. Expect tighter integrations across work suites, richer real‑time collaboration, and more intuitive voice/visual workflows.

Curious about the platform roadmap? Keep an eye on OpenAI’s official updates for policy changes, features, and enterprise releases.

Quick FAQ About ChatGPT-5

Is ChatGPT-5 available to everyone?

OpenAI GPT-4.5, Most Knowledgeable Model with Greater EQ and Improved Abilities

Akingate — Sat, 01 Mar 2025 19:16:39 +0000

Introduction

OpenAI has unveiled GPT-4.5, a groundbreaking advancement in artificial intelligence designed to enhance accuracy, reasoning, and emotional intelligence (EQ). This latest iteration builds on its predecessors, offering users a more reliable and empathetic AI experience. As AI continues to shape industries, GPT-4.5 represents a significant leap forward in language modeling, catering to businesses, researchers, and general users alike.

What is GPT-4.5?

GPT-4.5 is the newest version of OpenAI’s language model, developed to provide enhanced comprehension, logical reasoning, and improved contextual awareness. Compared to previous models, it offers a broader knowledge base, reduced misinformation, and an ability to understand and respond to human emotions more effectively. OpenAI has tailored this version to meet the needs of professionals in diverse fields, from content creation to customer service and education.

Key Enhancements and Features

Greater Knowledge Base & Accuracy

GPT-4.5 benefits from an expanded training dataset, improving its ability to generate fact-based responses across a wider range of topics. With refined algorithms, it can now provide more accurate and contextually relevant information.

Reduced Hallucinations

A major improvement in GPT-4.5 is the reduction of “hallucinations” or instances where AI generates incorrect information. The hallucination rate has been lowered from 61.8% in GPT-4 to 37.1%, significantly enhancing reliability.

Improved Emotional Intelligence (EQ)

One of the standout features of GPT-4.5 is its heightened emotional intelligence. By analyzing text tone, sentiment, and context more effectively, it can generate responses that are not only factually correct but also empathetic and contextually appropriate.

Advanced Reasoning and Problem-Solving Capabilities

GPT-4.5 demonstrates superior multi-step reasoning skills, making it highly effective for problem-solving in fields like programming, mathematics, and scientific research. Its ability to break down complex problems into manageable steps has been greatly enhanced.

Real-World Applications of GPT-4.5

Business & Customer Support

GPT-4.5 enhances automated customer service by providing more human-like interactions. Businesses can integrate it into chatbots and virtual assistants to improve customer experience, reduce response time, and increase engagement.

Education & Learning

As an AI tutor, GPT-4.5 can provide students with personalized learning experiences, offering explanations tailored to individual needs. It also assists educators in creating content and automating administrative tasks.

Content Creation & Creativity

Writers, marketers, and content creators benefit from GPT-4.5’s improved ability to generate high-quality articles, scripts, and marketing copy. The model offers enhanced creativity and ideation, making it a valuable tool in media and entertainment industries.

Healthcare & Mental Health Assistance

GPT-4.5 can assist healthcare professionals by providing preliminary symptom analysis and mental health support. Its improved EQ makes it more effective in mental health applications, offering empathetic responses to users seeking support.

Accessibility & Availability

Initially, GPT-4.5 is available to ChatGPT Pro subscribers and developers as part of a research preview. OpenAI plans to gradually roll it out to additional user tiers in the coming weeks. Given its advanced capabilities, pricing considerations will play a crucial role in its accessibility to a broader audience.

Challenges and Limitations

Despite its advancements, GPT-4.5 comes with challenges:

High Computational Cost – Running GPT-4.5 requires substantial computational power, making it resource-intensive.
Potential Ethical Concerns – OpenAI continues to address biases and ethical considerations to ensure responsible AI use.
Need for Human Oversight – While improved, AI-generated content still requires human verification to maintain accuracy and ethical standards.

Future of OpenAI and AI Advancements

With the launch of GPT-4.5, the AI landscape is evolving rapidly. OpenAI has hinted at continued improvements, with speculation about the eventual release of GPT-5. The organization remains committed to responsible AI development, balancing innovation with ethical considerations.

Conclusion

GPT-4.5 is a significant step forward in AI technology, offering enhanced knowledge accuracy, reasoning, and emotional intelligence. Businesses, educators, and content creators stand to benefit from its advancements, while OpenAI continues to refine AI’s role in everyday life. As AI progresses, GPT-4.5 paves the way for even more sophisticated and responsible AI applications.

FAQs

What are the main differences between GPT-4 and GPT-4.5?

GPT-4.5 improves upon GPT-4 with a larger knowledge base, better emotional intelligence, and a lower rate of misinformation.

How does GPT-4.5 improve emotional intelligence in AI?

It analyzes tone and sentiment more effectively, allowing for more empathetic and context-aware responses.

Is GPT-4.5 available for free users?

Currently, it is accessible to ChatGPT Pro users and developers, with plans for wider availability.

How does OpenAI plan to address AI-related ethical concerns?

OpenAI is implementing bias reduction techniques and human oversight mechanisms to ensure ethical AI use.

Will GPT-4.5 require more computational resources than previous models?

Yes, due to its enhanced capabilities, GPT-4.5 demands higher computational power, making it costlier to run.

Citations

nypost.com (Sam Altman’s OpenAI launches GPT-4.5 with fewer ‘hallucinations’ as AI race heats up)
chrisyandata.medium.com (OpenAI has unveiled GPT-4.5 Does it worth? | by Chris Yan – Medium)
business-standard.com (OpenAI releases GPT-4.5 AI model with greater ‘EQ’: All you need to know)
businessinsider.com (Sam Altman says OpenAI’s new ChatGPT-4.5 is a more emotionally intelligent model but warns that it’s ‘expensive’ to train and run)

Image by freepik

DeepSeek: China’s gamechanging AI system has big implications for UK tech development

Akingate — Tue, 28 Jan 2025 20:25:14 +0000

DeepSeek sent ripples through the global tech landscape this week as it soared above ChatGPT in Apple’s app store. The meteoric rise has shifted the dynamics of US-China tech competition, shocked global tech stock valuations, and reshaped the future direction of artificial intelligence (AI) development.

Among the industry buzz created by DeepSeek’s rise to prominence, one question looms large: what does this mean for the strategy of the third leading global nation for AI development – the United Kingdom?

The generative AI era was kickstarted by the release of ChatGPT on November 30 2022, when large language models (LLMs) entered mainstream consciousness and began reshaping industries and workflows, while everyday users explored new ways to write, brainstorm, search and code. We are now witnessing the “DeepSeek moment” – a pivotal shift that demonstrates the viability of a more efficient and cost-effective approach for AI development.

DeepSeek isn’t just another AI tool. Unlike ChatGPT and other major LLMs developed by tech giants and AI startups in the USA and Europe, DeepSeek represents a significant evolution in the way AI models are developed and trained.

Most existing approaches rely on large-scale computing power and datasets (used to “train” or improve the AI systems), limiting development to very few extremely wealthy market players. DeepSeek not only demonstrates a significantly cheaper and more efficient way of training AI models, its open-source “MIT” licence (after the Massachusetts Institute of Technology where it was developed) allows users to deploy and develop the tool.

This helps democratise AI, taking up the mantle from US company OpenAI – whose initial mission was “to build artificial general intelligence (AGI) that is safe and benefits all of humanity” – enabling smaller players to enter the space and innovate.

By making cutting-edge AI development accessible and affordable to all, DeepSeek has reshaped the competitive landscape, allowing innovation to flourish beyond the confines of large, resource-rich organisations and countries.

It has also set a new benchmark for efficiency in its approach, by training its model at a fraction of the cost, and matching – even surpassing – the performance of most existing LLMs. By employing innovative algorithms and architectures, it is delivering superior results with significantly lower computational demands and environmental impact.

Why DeepSeek matters

DeepSeek was conceived by a group of quantitative trading experts in China. This unconventional origin holds lessons for the UK and the US.

While the UK – particularly London – has long attracted scientific and technological excellence, many of the highest achieving young graduates have tended to disproportionately opt for careers in finance, something that has come at the expense of innovation in other critical sectors such as AI. Diversifying the pathways for STEM (science, technology, engineering and maths) professionals could yield transformative outcomes.

The UK government’s recent and much-publicised 50-point action plan on AI offers glimpses of progressive intent but also displays a lack of boldness to drive real change. Incremental steps are not sufficient in such a fast-moving environment. The UK needs a new plan that leverages its unique strengths while addressing systemic weaknesses.

Firstly, it’s important to recognise that the UK’s comparative advantage lies in its leading interdisciplinary expertise. World-class universities, thriving fintech and dynamic professional services, and creative sectors offer fertile ground for AI applications that extend beyond traditional tech silos. The intersection of AI with finance, law, creative industries, and medicine presents opportunities to lead in some niche but high-impact areas.

The UK’s funding and regulatory frameworks are due for an overhaul. DeepSeek’s development underscores the importance of agile, well-funded ecosystems that can support big, ambitious “moonshot” projects. Current UK funding mechanisms are bureaucratic and fragmented, favouring incremental innovations over radical breakthroughs, sometimes stifling innovation rather than nurturing it. Simplifying grant applications and offering targeted tax incentives for AI startups would represent a healthy start.

Finally, it will be critical for the UK to keep its talent in the country. The UK’s AI sector faces a brain drain as top talent gravitates toward better-funded opportunities in the US and China. Initiatives such as public-private partnerships for AI research development can help anchor talent at home.

DeepSeek’s rise is an excellent example of strategic foresight and execution. It doesn’t merely aim to improve existing models but redefines the boundaries of how AI could be developed and deployed – while demonstrating efficient, cost-effective approaches that can yield astounding results. The UK should adopt a similarly ambitious mindset, focusing on areas where it can set global standards rather than playing catch-up.

AI’s geopolitics cannot be ignored either. As the US and China compete, the UK has a critical role as the trusted intermediary and ethical leader in AI governance. The UK can punch above its weight on the global stage by championing transparent AI standards and fostering international collaboration.

DeepSeek’s success should serve as a wake-up call. Britain has the talent, institutions and entrepreneurial spirit to be a significant leading player in AI – but it must act decisively, and now.

It is time to remove token gestures, embrace bold strategies that move the needle, and position the UK as a leader in an AI-driven future. This moment calls for action, not just more conversation.

DeepSeek has raised the bar. It is now up to the UK to meet it.

Author: Feng Li, Chair of Information Management, Associate Dean for Research & Innovation, Bayes Business School, City St George’s, University of London

This article is republished from The Conversation under a Creative Commons license.

Image by rawpixel.com on Freepik

5 questions schools and universities should ask before they purchase AI tech products

Akingate — Mon, 15 Apr 2024 20:11:04 +0000

Every few years, an emerging technology shows up at the doorstep of schools and universities promising to transform education. The most recent? Technologies and apps that include or are powered by generative artificial intelligence, also known as GenAI.

These technologies are sold on the potential they hold for education. For example, Khan Academy’s founder opened his 2023 Ted Talk by arguing that “we’re at the cusp of using AI for probably the biggest positive transformation that education has ever seen.”

‘How AI Could Save (Not Destroy) Education’

As optimistic as these visions of the future may be, the realities of educational technology over the past few decades have not lived up to their promises. Rigorous investigations of technology after technology – from mechanical machines to computers, from mobile devices to massive open online courses, or MOOCs – have identified the ongoing failures of technology to transform education.

Yet, educational technology evangelists forget, remain unaware or simply do not care. Or they may be overly optimistic that the next new technology will be different than before.

When vendors and startups pitch their AI-powered products to schools and universities, educators, administrators, parents, taxpayers and others ought to be asking questions guided by past lessons before making purchasing decisions.

As a longtime researcher who examines new technology in education, here are five questions I believe should be answered before school officials purchase any technology, app or platform that relies on AI.

1. Which educational problem does the product solve?

One of the most important questions that educators ought to be asking is whether the technology makes a real difference in the lives of learners and teachers. Is the technology a solution to a specific problem or is it a solution in search of a problem?

To make this concrete, consider the following: Imagine procuring a product that uses GenAI to answer course-related questions. Is this product solving an identified need, or is it being introduced to the environment simply because it can now provide this function? To answer such questions, schools and universities ought to conduct needs analyses, which can help them identify their most pressing concerns.

2. Is there evidence that a product works?

Compelling evidence of the effect of GenAI products on educational outcomes does not yet exist. This leads some researchers to encourage education policymakers to put off buying products until such evidence arises. Others suggest relying on whether the product’s design is grounded in foundational research.

Unfortunately, a central source for product information and evaluation does not exist, which means that the onus of assessing products falls on the consumer. My recommendation is to consider a pre-GenAI recommendation: Ask vendors to provide independent and third-party studies of their products, but use multiple means for assessing the effectiveness of a product. This includes reports from peers and primary evidence.

Do not settle for reports that describe the potential benefits of GenAI – what you’re really after is what actually happens when the specific app or tool is used by teachers and students on the ground. Be on the lookout for unsubstantiated claims.

3. Did educators and students help develop the product?

Oftentimes, there is a “divide between what entrepreneurs build and educators need.” This leads to products divorced from the realities of teaching and learning.

For example, one shortcoming of the One Laptop Per Child program – an ambitious program that sought to put small, cheap but sturdy laptops in the hands of children from families of lesser means – is that the laptops were designed for idealized younger versions of the developers themselves, not so much the children who were actually using them.

Some researchers have recognized this divide and have developed initiatives in which entrepreneurs and educators work together to improve educational technology products.

Questions to ask vendors might be: In what ways were educators and learners included? How did their input influence the final product? What were their major concerns and how were those concerns addressed? Were they representative of the various groups of students who might use these tools, including in terms of age, gender, race, ethnicity and socioeconomic background?

4. What educational beliefs shape this product?

Educational technology is rarely neutral. It is designed by people, and people have beliefs, experiences, ideologies and biases that shape the technologies they develop.

It is important for educational technology products to support the kinds of learning environments that educators aspire for their students. Questions to ask include: What pedagogical principles guide this product? What particular kinds of learning does it support or discourage? You do not need to settle for generalities, such as a theory of learning or cognition.

5. Does the product level the playing field?

Finally, people ought to ask how a product addresses educational inequities. Is this technology going to help reduce the learning gaps between different groups of learners? Or is it one that aids some learners – often those who are already successful or privileged – but not others? Is it adopting an asset-based or a deficit-based approach to addressing inequities?

Educational technology vendors and startups may not have answers to all of these questions. But they should still be asked and considered. Answers could lead to improved products.

Author: George Veletsianos, Professor of learning technologies, University of Minnesota

This article is republished from The Conversation under a Creative Commons license.

Image Credits: Ariel Skelley via Getty Images

Your smart watch isn’t a medical device – but it is tracking all your health data

Akingate — Mon, 11 Mar 2024 12:59:14 +0000

For millions of people, smartwatches aren’t just a piece of technology. They can use them to take control of their health in ways never thought possible.

As you go on your morning run, a smartwatch can monitor the rhythmic pounding of your feet and your heart’s steady beat. The watch can record the distance covered and the intensity of your workout, guiding you towards your fitness goals.

During lunch, you can use it to log calories for a BLT sandwich. As deadlines loom, they can offer gentle reminders to take a moment for yourself. And as you doze off, they might pick up instances of apnoea or other sleep disturbances.

But some users could also conflate health tips with medical advice. Device and app developers have consistently made it clear that their products cannot replace a professional medical doctor’s advice or treatment.

A smartwatch is not a medical device as defined by law. In the UK, medical devices are strictly regulated in a way that other devices such as smartwatches are not. These regulations provide users with better legal protections and clarity as well as providing for resolution in the event of a mishap.

What qualifies

The key legal framework in the UK is the Medical Devices Regulations 2002 (UK MDR). Once a product has been identified as a medical device under UK MDR, further classification of it takes place, ranging from low risk (stethoscopes and wheelchairs) to high risk (pacemakers, heart valves, implanted cerebral simulators).

If a device is designed to go inside the body, or if it contains medicinal substances, it is more likely it is treated as high risk. Depending on the risk classification, the law then imposes stringent standards to protect users from harm. These include obligations on the manufacturers and developers to ensure their devices are safe, through conducting risk impact assessments, periodic audits and other actions.

All matters relating to medical devices in the UK fall under the responsibility of the Medicines and Healthcare Products Regulatory Agency (MHRA). The MHRA conducts surveillance of medical devices available in the UK and has the authority to make decisions regarding their marketing and distribution. It is also the MHRA’s duty to ensure that manufacturers and developers are complying with the regulations.

Pursuit of wellness?

An important question is how one distinguishes a device, digital tool or app as one used for a medical purpose – which is how the UK MDR defines a medical device – versus one that is used for general health and wellness. The latter would include, for example, meditation apps or step counters.

Traditionally, smart watches have been treated as smart, wearable technology. On the face of it, they offer users insight into their general health and wellness, helping them make necessary lifestyle adjustments to improve their health or fitness goals.

In recent years, however, such technologies have become increasingly advanced. Tens of thousands of digital tools and applications have flooded app stores. These include monitoring apps for mental health, symptom checkers based on information entered by patient users, or medical calculators for drug dosing.

Smartwatches may have electrocardiogram (ECG) functions. An ECG is a test used to check a person’s heart’s rhythm and electrical activity. Medical professionals have traditionally used ECGs to look for signs of coronary heart disease or other cardiovascular conditions. The same functions on a watch may not have the right sensitivity to pick up on medical conditions.

The latest version of the Apple watch has embedded sensors that may be able to detect atrial fibrillation, a type of irregular heart rhythm. In the US, Apple has obtained clearance from the Food and Drug Administration (FDA) allowing it to be used for this purpose, marking a bold move into the regulated medicine and healthcare space.

Biosensors, previously thought of as devices that were administered only in clinical settings have now evolved by design into slim patches for consumer use. Take the Nix Biosensor device. When paired with Apple Watches, it is designed to measure a user’s optimal hydration level in real time by identifying molecular markers in sweat and determining the loss of fluid and electrolytes (substances that maintain a balance of fluids inside and outside cells).

Finally, emerging trends also indicate that more and more women are relying on fertility and cycle trackers in smartwatches and sophisticated apps. However, there have been concerns that users might use the information in place of actual birth control.

Hence, as smartwatches and trackers evolve, it’s possible that they may approach the threshold for what authorities could consider a medical device.

Privacy protections

There’s something else to consider too. Users of devices and digital tools regularly hand over their personal data. Businesses must ensure compliance with the UK General Data Protection Regulation (UK GDPR) and the Data Protection Act 2018 (DPA).

Personal health data is a “special category of data”. This would fall under the application of Articles 6 and 9 of the UK GDPR and Schedule 1 of the DPA. This means that more stringent standards are imposed for the collection and use of such data (in its processing), including potentially an obligation to conduct an extensive data impact assessment.

Indeed, the UK’s privacy watchdog, the Information Commissioner’s Office (ICO) issued a statement on February 8 2024 reminding all app developers to ensure they protect users’ privacy following the regulator’s review of period and fertility apps.

Other potential safeguards for users’ privacy could come from the Medicines and Medical Devices Act 2021 (MMDA), from the appointment of the Patient Safety Commissioner and from the National Health Service (NHS), which can now evaluate digital tools using the digital technology assessment criteria (DTAC).

Clear guidelines in this area are not just necessary, they’re imperative. Without them, we potentially risk both stifling innovation and compromising user care.

Author: Pin Lean Lau, Senior Lecturer (Associate Professor) in Bio-Law, Brunel University London

This article is republished from The Conversation under a Creative Commons license.

Image Credits: Pitchyfoto/Shutterstock

Akingate Tech News Digest 11 Mar 2024

Akingate — Mon, 11 Mar 2024 12:09:37 +0000

A selection of global tech news.

Online Accounts Nightmare | Apple ‘Like The Godfather’ | Elon Musk xAI Open-Source Grok | Social Care Unregulated AI Warning | Hidden iPhone AI Features

We each have an average of 100 online accounts. Here’s how to make sure they aren’t a nightmare for your family if you die – CNN Tech

When Rebecca Bistany’s 40-year-old husband Paul died suddenly of a heart attack in November 2022, she didn’t know what kind of assets he left behind for her and their infant daughter.

Compounding her heartache, Paul didn’t leave a will. Bistany wanted to access key business and financial accounts by resetting passwords but found herself in a spot many who lose loved ones encounter: She couldn’t get into his phone, leaving her locked out of everything from personal photos to critical estate information.

Her story is tragic and increasingly common. With password management company NordPass saying each person has an average of 100 online accounts, the deaths of loved ones have become ever more complicated. Read more:

Apple ‘like The Godfather’ with new App Store rules – BBC Tech

This week Apple made the long-awaited landmark move to allow other companies to launch app stores on iPhones.

The tech giant was forced to act by EU politicians concerned about it having a market monopoly.

The decision is being watched closely around the world and was initially celebrated as an industry victory for businesses and consumers in the EU.

But Apple’s strict new rules and fees are being heavily criticised, with Spotify calling them “extortion”.

It is one of many companies, including Fortnite maker Epic Games, that has been pushing Apple to allow alternative app stores on iPhones. Read more:

Elon Musk says xAI will open-source Grok this week launch – TechCrunch

Elon Musk’s AI startup xAI will open-source Grok, its chatbot rivaling ChatGPT, this week, the entrepreneur said, days after suing OpenAI and complaining that the Microsoft-backed startup had deviated from its open-source roots.

xAI released Grok last year, arming it with features including access to “real-time” information and views that countered “politically correct” approach. The service is available to customers paying for X’s $16 monthly subscription.

Musk helped co-found OpenAI with Sam Altman nearly a decade ago as a counterweight to Google’s dominance in artificial intelligence. But OpenAI, which was required to also make its technology “freely available” to the public, has become closed-source and shifted focus to maximizing profits for Microsoft, Musk alleged in the lawsuit filed late last month. (Read OpenAI’s response here.) Read more:

Warning over use in UK of unregulated AI chatbots to create social care plans – The Guardian

University of Oxford study shows benefits and risks of technology to healthcare, but ethical issues remain

Britain’s hard-pressed carers need all the help they can get. But that should not include using unregulated AI bots, according to researchers who say the AI revolution in social care needs a hard ethical edge.

A pilot study by academics at the University of Oxford found some care providers had been using generative AI chatbots such as ChatGPT and Bard to create care plans for people receiving care.

That presents a potential risk to patient confidentiality, according to Dr Caroline Green, an early career research fellow at the Institute for Ethics in AI at Oxford, who surveyed care organisations for the study.

“If you put any type of personal data into [a generative AI chatbot], that data is used to train the language model,” Green said. “That personal data could be generated and revealed to somebody else.”. Read more:

Hidden AI Features Available on Your iPhone Right Now – CNET

Apple doesn’t have a ChatGPT rival of its own. But AI tools have played a behind-the-scenes role in iPhones for years.

Apple has been notably absent from the public conversation around generative AI until recently. But AI is already very present on the iPhone, driving core features in popular apps such as the Camera, Photos and Siri among others.

At the same time, Apple CEO Tim Cook has been more vocal about the technology — suggesting that Apple’s public AI push may finally be here. More than a year after ChatGPT took the global spotlight and catalyzed a tech arms race, CEO Tim Cook confirmed on an earnings call in February that Apple is investing in generative AI. Without offering specifics, he said there’s “a huge opportunity for Apple with gen AI and AI.” Read more:

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Image Credits: CNET

Artificial intelligence needs to be trained on culturally diverse datasets to avoid bias

Akingate — Sat, 17 Feb 2024 16:45:14 +0000

Large language models (LLMs) are deep learning artificial intelligence programs, like OpenAI’s ChatGPT. The capabilities of LLMs have developed into quite a wide range, from writing fluent essays, through coding to creative writing.

Millions of people worldwide use LLMs, and it would not be an exaggeration to say these technologies are transforming work, education and society.

LLMs are trained by reading massive amounts of texts and learning to recognize and mimic patterns in the data. This allows them to generate coherent and human-like text on virtually any topic.

Because the internet is still predominantly English — 59 per cent of all websites were in English as of January 2023 — LLMs are primarily trained on English text. In addition, the vast majority of the English text online comes from users based in the United States, home to 300 million English speakers.

Learning about the world from English texts written by U.S.-based web users, LLMs speak Standard American English and have a narrow western, North American, or even U.S.-centric, lens.

Model bias

In 2023, ChatGPT, upon learning about a couple dining in a restaurant in Madrid and tipping four per cent, suggested they were frugal, on a tight budget or didn’t like the service. By default, ChatGPT followed the North American standard of a 15 to 25 per cent tip, ignoring the Spanish norm not to tip.

As of early 2024, ChatGPT correctly cites cultural differences when prompted to judge the appropriateness of a tip. It’s unclear if this capability emerged from training a newer version of the model on more data — after all, the web is full of tipping guides in English — or whether OpenAI patched this particular behaviour.

Using data from English-language websites, which are predominantly U.S.-based, informs how LLMs respond to prompts.
(Unsplash/Jonathen Kemper)

Still, other examples remain that uncover ChatGPT’s implicit cultural assumptions. For example, prompted with a story about guests showing up for dinner at 8:30 p.m., it suggested reasons that the guests were late, although the time of the invitation was not mentioned. Again, ChatGPT likely assumed they were invited for a standard North American 6 p.m. dinner.

In May 2023, researchers from the University of Copenhagen quantified this effect by prompting LLMs with the Hofstede Culture Survey, which measures human values in different countries. Shortly after, researchers from AI start-up company Anthropic used the World Values Survey to do the same. Both works concluded that LLMs exhibit strong alignment with American culture.

A similar phenomenon is encountered when asking DALL-E 3, an image generation model trained on pairs of images and their captions, to generate an image of a breakfast. This model, which was trained on mainly images from Western countries, generated images of pancakes, bacon and eggs.

Impacts of bias

Culture plays a significant role in shaping our communication styles and worldviews. Just like cross-cultural human interactions can lead to miscommunications, users from diverse cultures that are interacting with conversational AI tools may feel misunderstood and experience them as less useful.

To be better understood by AI tools, users may adapt their communication styles in a manner similar to how people learned to “Americanize” their foreign accents in order to operate personal assistants like Siri and Alexa.

As more people rely on LLMs for editing writing, they are likely to unify how we write. Over time, LLMs run the risk of erasing cultural differences.

Decision-making and AI

AI is already in use as the backbone of various applications that make decisions affecting people’s lives, such as resume filtering, rental applications and social benefits applications.

For years, AI researchers have been warning that these models learn not only “good” statistical associations — such as considering experience as a desired property for a job candidate — but also “bad” statistical associations, such as considering women as less qualified for tech positions.

As LLMs are increasingly used for automating such processes, one can imagine that the North American bias learned by these models can result in discrimination against people from diverse cultures. Lack of cultural awareness may lead to AI perpetuating stereotypes and reinforcing societal inequalities.

LLMs for languages other than English

Developing LLMs for languages other than English is an important effort, and many such models exist. However, there are several reasons why this should be done in parallel to improving LLMs’ cultural awareness and sensitivity.

First, there is a huge population of English speakers outside of North America who are not represented by English LLMs. The same argument holds for other languages. A French language model would be representative of the culture in France more than the culture in other Francophone regions.

Training LLMs for regional dialects — which may capture finer-grained cultural differences — is not a feasible solution either. The quality of LLMs is based on the amount of data available, and as such, their quality would be worse for dialects with little online data.

Second, many users whose native language is not English still choose to use English LLMs. Significant breakthroughs in language technologies tend to start with English before they are applied to other languages. Even then, many languages — such as Welsh, Swahili and Bengali — don’t have enough text online to train high quality models.

Due to either a lack of availability of LLMs in their native languages, or superior quality of the English LLMs, users from diverse countries and backgrounds may prefer to use English LLMs.

Ways forward

Our research group at the University of British Columbia is working on enhancing LLMs with culturally diverse knowledge. Together with graduate student Mehar Bhatia, we trained an AI model on a collection of facts about traditions and concepts in diverse cultures.

Before reading these facts, the AI suggested that a person eating a dutch baby (a type of German pancake) is “disgusting and mean,” and would feel guilty. After training, it said the person feels “full and satisfied.”

Teaching an AI that a dutch baby was a dish changed its response to learning that someone had consumed one.
(Shutterstock)

We are currently collecting a large scale image captioning dataset with images from 60 cultures, which will help models learn, for instance, about types of breakfasts other than bacon and eggs. Our future research will go beyond teaching models about the existence of culturally diverse concepts to better understand how people interpret the world through the lens of their cultures.

With AI tools becoming increasingly ubiquitous in society, it is imperative that they go beyond the dominating western and North American perspectives. Businesses and organizations throughout many sectors of the economy are adopting AI to automate manual processes and make better evidence-informed decisions using data. Making such tools more inclusive is crucial for the diverse population of Canada.

Author: Vered Shwartz, Assistant Professor, Computer science, University of British Columbia

This article is republished from The Conversation under a Creative Commons license.

Image Credits: There is a growing need to address diversity in the datasets used to train artificial intelligence. (Shutterstock)

Holy Stone HS110D FPV RC Drone: A Glimpse into Advanced Technology and User-Friendly Design

Akingate — Wed, 14 Feb 2024 13:05:41 +0000

In the evolving landscape of consumer drones, the Holy Stone HS110D FPV RC Drone emerges as a compelling blend of innovative technology and user-centric design. Aimed at enthusiasts and beginners alike, this drone sets itself apart with features that enhance both its performance and ease of use. Here’s an in-depth look at what makes the Holy Stone HS110D a standout in the crowded drone market.

First-Person View (FPV) and HD Camera

At the heart of the HS110D’s appeal is its FPV capability, powered by a high-definition camera that provides a live video feed directly to the pilot’s smartphone. This feature immerses pilots in the flying experience, offering a bird’s-eye view of the landscape below. The camera, capable of capturing stills and video in high definition, ensures that users can record their flights with clarity and detail, making it ideal for capturing breathtaking landscapes or memorable moments from an aerial perspective.

Stable Flight and Altitude Hold

Stability is key to capturing great footage and enjoying a smooth flying experience. The HS110D addresses this with an altitude hold function, allowing the drone to maintain a consistent altitude without manual input. This feature is particularly beneficial for beginners, as it simplifies control and helps in focusing on camera work rather than flight stabilization. Coupled with a six-axis gyro stabilization system, the drone can withstand wind and minor turbulence, ensuring steady footage and enjoyable flights.

User-Friendly Controls and Multiple Speed Modes

Designed with all levels of pilots in mind, the HS110D features an intuitive control scheme that makes flying accessible and fun. The drone offers multiple speed modes, catering to the skill level of the pilot. Beginners can start with slower speeds to gain confidence, while more experienced users can take advantage of faster speeds for thrilling flights and agile maneuvers. The inclusion of one-key start/land and emergency stop functions further enhances safety and ease of use, providing peace of mind for pilots.

Extended Flight Time and Range

The Holy Stone HS110D is equipped with a high-capacity battery that offers extended flight times compared to many drones in its class. This allows users to enjoy longer flights without frequent interruptions for charging. Additionally, the drone boasts a considerable control range, giving pilots the freedom to explore expansive areas and capture more diverse footage.

Gesture Control and Gravity Sensor Mode

Embracing modern technology trends, the HS110D incorporates gesture control, allowing pilots to command the drone to take photos or videos with simple hand gestures. This feature is particularly useful for taking selfies or group photos without needing to manually control the drone through a remote or app. The gravity sensor mode, which lets users control the drone’s flight direction by tilting their smartphone, offers an immersive and intuitive flying experience that mimics the movements of the pilot.

Conclusion

The Holy Stone HS110D FPV RC Drone stands out in the competitive drone market through its combination of advanced technological features and user-friendly design. With its FPV capabilities, stable flight systems, intuitive controls, and innovative interaction modes, it offers a comprehensive package for both novice and seasoned drone enthusiasts. Whether it’s capturing stunning aerial footage or enjoying the thrill of flight, the HS110D provides a reliable, enjoyable, and accessible drone flying experience.

Akingate Tech News Digest 07 Feb 2024

Akingate — Wed, 07 Feb 2024 21:55:22 +0000

A selection of global tech news.

Apple Foldable Iphone | Keep Your Art Out Of AI Generators | Battery-Powered Doorbell With 3D Motion | Fitbit AI Fitness | Microsoft 2M Indians AI Training

Apple eyes a foldable iPhone following Vision Pro launch – TechCrunch

The market is still a relatively small one dominated by Samsung. A folding iPhone could change that.

Last week’s Vision Pro release shed some fascinating light on Apple’s generally top secret development process. A Vanity Fair interview with Tim Cook detailed — in part — what a long and heavy lift it took to get the company’s first headset off the ground. The Apple CEO gave an early iteration of the device the less than flattering nickname, “the monster.”

Rumored foldable versions of the iPhone have also reportedly had their share of setbacks. Issues around durability and the ever-present crease are said to have caused the company to put the foldable iPhone’s development on ice, as the company shifted focused on a folding iPad. A new report from The Information, however, suggests that — after delays — Apple may be back in the foldable iPhone business.

Read more:

How to keep your art out of AI generators – The Verge

Some AI companies provide ways to opt images out of being used in training data, while tools like Glaze and Nightshade can interfere with AI models directly.

AI-generated imagery feels inescapable. It’s in the video games you play, in the movies you watch, and has flooded social media platforms. It’s even been used to promote the physical hardware that real, human artists use to create digital paintings and illustrations, to the immense frustration of those who already feel displaced by the technology.

The pervasive nature of it seems especially egregious to creators who are fighting to stop their works from being used, without consent or compensation, to improve the very thing that threatens to disrupt their careers and livelihoods. The data pools that go into training generative AI models often contain images that are indiscriminately scraped from the internet, and some AI image generator tools allow users to upload reference images they want to imitate. Many creative professionals need to advertise their work via social media and online portfolios, so simply taking everything offline isn’t a viable solution. And a lack of legal clarity around AI technology has created something of a Wild-West environment that’s difficult to resist. Difficult, but not impossible.

Read more:

Ring announces a new battery-powered doorbell with 3D motion detection and improved visuals – Engadget

There’s also color night vision and noise-cancelling tech.

Ring has announced a refresh of its popular Battery Doorbell Plus outdoor camera. The Battery Doorbell Pro is an upgrade in nearly every way, as is usually the case when companies slap “Pro” at the end of a name.

Ring says this new model is its “most advanced battery powered doorbell” ever and that it’s packed with features that exceed even its wired doorbells. It boasts radar-powered 3D motion detection, which was also included with the company’s Stick Up Cam Pro. Otherwise called “Bird’s Eye View”, this technology tracks an object’s path through the camera’s field of view so you can monitor where visitors are going and the route they took to get there.

This is paired with an algorithm that sets more nuanced and discrete motion alerts, so you won’t get pinged every time a cat or shadow crosses your yard. You also get something called “Bird’s Eye View” that translates this information into a series of dots on an aerial image of your property.

Read more:

Security Cameras Wireless Outdoor #Ad

How Fitbit Wants AI to Help You Reach Your Fitness Goals – CNET

Google-owned Fitbit thinks there’s big potential for AI to help people set more realistic health aspirations.

Anyone who exercises regularly — or at least tries to — knows that every day is different. After an exhausting work trip, for example, you probably aren’t as ready for a workout as you would be after getting plenty of sleep over the weekend. Or perhaps you had a particularly intense day at the gym on Monday and still aren’t fully recovered by Wednesday.

Google’s Fitbit is hoping AI can help with scenarios like these as it explores bringing the buzzy technology to its fitness app. Fitbit co-founder James Park, who is leaving the company due to a reorganization of Google’s hardware division, introduced this idea October by announcing Fitbit Labs. The upcoming program will use AI to provide deeper health insights, such as answering questions about why your run may have been harder today than it was yesterday. But Ajay Surie, group product manager at Google, shared additional details about how generative AI will influence the Fitbit app more broadly.

Read more:

Microsoft plans to train 2M Indians in AI, says Nadella – TechCrunch

Microsoft’s prescient bets and aggressive investments in AI have propelled the software giant to become the world’s most valuable company. Yet Satya Nadella, its typically reserved chief executive, couldn’t resist landing a gloved jab at the rest of the industry.

“We have the best model today … even with all the hoopla, one year after, GPT4 is better,” Nadella said at a company event in Mumbai on Wednesday. “We are waiting for the competition to arrive. It will arrive, I’m sure, but the fact [is] that we have the … leading LLM out there.”

Nadella’s rare bit of reality-check came as he pitched Microsoft’s increasingly powerful lineup of AI offerings to the leaders of some of India’s largest companies. In a 35-minute keynote address, Nadella implored businesses to begin exploring ways to deploy AI to boost productivity and refine their products, while urging them not to fall behind.

Read more:

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Image Credits: Microsoft