Mashable offers a hands-on guide to help users detect AI-generated videos by observing subtle technical cues. Key warning signs include mismatched lip movements and speech, where voices are dubbed over real footage and audio isn’t perfectly aligned with mouth motions.
Users are also advised to look for visual anomalies such as unnatural blurs, distorted shadows or odd lighting effects that seem inconsistent with natural environments. Deepfake videos can show slight flickers around faces or uneven reflections that betray their artificial origin.
Blinking, or the lack thereof, can also be revealing. AI faces often fail to replicate natural blinking patterns, and may display either no blinking or irregular frequency.
Viewers should also note unnatural head or body movements that do not align with speech or emotional expression, such as stiff postures or awkward gestures.
Experts stress these cues are increasingly well-engineered, making deepfakes harder to detect visually. They recommend combining observation with source verification, such as tracing the video back to reputable outlets or conducting reverse image searches for robust protection.
Ultimately, better detection tools and digital media literacy are essential to maintaining trust in online content.
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The Instagram accounts of Adele, Future, Tyla, and Michael Jackson were hacked late Thursday to promote an unauthorised meme coin. Posts showed an AI image of the Future with a ‘FREEBANDZ’ coin, falsely suggesting ties to the rapper.
The token, launched on the Solana platform Pump.fun, surged briefly to nearly $900,000 in market value before collapsing by 98% after its creator dumped 700 million tokens. The scheme netted more than $49,000 in Solana for the perpetrator, suspected of being behind the account hijackings.
None of the affected celebrities has issued a statement, while Future’s Instagram account remains deactivated. The hack continues a trend of using celebrity accounts for crypto pump-and-dump schemes. Previous cases involved the UFC, Barack Obama, and Elon Musk.
Such scams are becoming increasingly common, with attackers exploiting the visibility of major social media accounts to drive short-lived token gains before leaving investors with losses.
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The discovery of hundreds of non-consensual deepfake images on a student’s laptop at the University of Hong Kong has reignited debate about privacy, technology, and accountability. The scandal echoes the 2008 Edison Chen photo leak, which exposed gaps in law and gender double standards.
Unlike stolen private images, today’s fabrications are AI-generated composites that can tarnish reputations with a single photo scraped from social media. The dismissal that such content is ‘not real’ fails to address the damage caused by its existence.
The legal system of Hong Kong struggles to keep pace with this shift. Its privacy ordinance, drafted in the 1990s, was not designed for machine-learning fabrications, while traditional harassment and defamation laws predate the advent of AI. Victims risk harm before distribution is even proven.
The city’s privacy watchdog has launched a criminal investigation, but questions remain over whether creation or possession of deepfakes is covered by existing statutes. Critics warn that overreach could suppress legitimate uses, yet inaction leaves space for abuse.
Observers argue that just as the snapshot camera spurred the development of modern privacy law, deepfakes must drive a new legal boundary to safeguard dignity. Without reform, victims may continue facing harm without recourse.
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According to sworn interrogations, OpenAI said Musk had discussed possible financing arrangements with Zuckerberg as part of the bid. Musk’s AI startup xAI, a competitor to OpenAI, did not respond to requests for comment.
In the filing, OpenAI asked a federal judge to order Meta to provide documents related to any bid for OpenAI, including internal communications about restructuring or recapitalisation. The firm argued these records could clarify motivations behind the bid.
Meta countered that such documents were irrelevant and suggested OpenAI seek them directly from Musk or xAI. A US judge ruled that Musk must face OpenAI’s claims of attempting to harm the company through public remarks and what it described as a sham takeover attempt.
The legal dispute follows Musk’s lawsuit against OpenAI and Sam Altman over its for-profit transition, with OpenAI filing a countersuit in April. A jury trial is scheduled for spring 2026.
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College students are increasingly turning to AI chatbots for emotional support, prompting concern among mental health professionals. A 2025 report ranked ‘therapy and companionship’ as the top use case for generative AI, particularly among younger users.
Studies by MIT and OpenAI show that frequent AI use can lower social confidence and increase avoidance of face-to-face interaction. On campuses, digital mental health platforms now supplement counselling services, offering tools that identify at-risk students and provide basic support.
Experts warn that chatbot companionship may create emotional habits that lack grounding in reality and hinder social skill development. Counsellors advocate for educating students on safe AI use and suggest universities adopt tools that flag risky engagement patterns.
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OpenAI’s rollout of GPT-5 has faced criticism from users attached to older models, who say the new version lacks the character of its predecessors.
GPT-5 was designed as an all-in-one model, featuring a lightweight version for rapid responses and a reasoning version for complex tasks. A routing system determines which option to use, although users can manually select from several alternatives.
Modes include Auto, Fast, Thinking, Thinking mini, and Pro, with the last available to Pro subscribers for $200 monthly. Standard paid users can still access GPT-4o, GPT-4.1, 4o-mini, and even 3o through additional settings.
Chief executive Sam Altman has said the long-term goal is to give users more control over ChatGPT’s personality, making customisation a solution to concerns about style. He promised ample notice before permanently retiring older models.
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The Commonwealth Bank of Australia has reversed plans to cut 45 customer service roles following union pressure over the use of AI in its call centres.
The Finance Sector Union argued that CBA was not transparent about call volumes, taking the case to the Workplace Relations Tribunal. Staff reported rising workloads despite claims that the bank’s voice bot reduced calls by 2,000 weekly.
CBA admitted its redundancy assessment was flawed, stating that it had not fully considered the business needs. Impacted employees are being offered the option to remain in their current roles, relocate within the firm, or depart.
The Bank of Australia apologised and pledged to review internal processes. Chief executive Matt Comyn has promoted AI adoption, including a new partnership with OpenAI, but the union called the reversal a ‘massive win’ for workers.
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Communication, empathy, and judgment were dismissed for years as ‘soft skills‘, sidelined while technical expertise dominated training and promotion. A new perspective argues that these human competencies are fundamental to resilience and transformation.
Researchers and practitioners emphasise that AI can expedite decision-making but cannot replace human judgment, trust, or narrative. Failures in leadership often stem from a lack of human capacity rather than technical gaps.
Redefining skills like decision-making, adaptability, and emotional intelligence as measurable behaviours helps organisations train and evaluate leaders effectively. Embedding these human disciplines ensures transformation holds under pressure and uncertainty.
Career and cultures are strengthened when leaders are assessed on their ability to build trust, resolve conflicts, and influence through storytelling. Without funding the human core alongside technical skills, strategies collapse, and talent disengages.
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Chief of Microsoft AI, Mustafa Suleyman, has urged AI firms to stop suggesting their models are conscious, warning of growing risks from unhealthy human attachments to AI systems.
In a blog post, he described the phenomenon as Seemingly Conscious AI, where models mimic human responses convincingly enough to give users the illusion of feeling and thought. He cautioned that this could fuel AI rights, welfare, or citizenship advocacy.
Suleyman stressed that such beliefs could emerge even among people without prior mental health issues. He called on the industry to develop guardrails that prevent or counter perceptions of AI consciousness.
AI companions, a fast-growing product category, were highlighted as requiring urgent safeguards. Microsoft AI chief’s comments follow recent controversies, including OpenAI’s decision to temporarily deprecate GPT-4o, which drew protests from users emotionally attached to the model.
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A new study reveals that prominent AI models now show a marked preference for AI‑generated content over that created by humans.
Tests involving GPT‑3.5, GPT-4 and Llama 3.1 demonstrated a consistent bias, with models selecting AI‑authored text significantly more often than human‑written equivalents.
Researchers warn this tendency could marginalise human creativity, especially in fields like education, hiring and the arts, where original thought is crucial.
There are concerns that such bias may arise not by accident but by design flaws embedded within the development of these systems.
Policymakers and developers are urged to tackle this bias head‑on to ensure future AI complements rather than replaces human contribution.
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