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.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
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.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
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.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
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.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
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.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
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.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
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.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
A new study from Arizona State University researchers suggests that chain-of-thought reasoning in large language models (LLMs) is closer to pattern matching than accurate logical inference. The findings challenge assumptions about human-like intelligence in these systems.
The researchers used a data distribution lens to examine where chain-of-thought fails, testing models on new tasks, different reasoning lengths, and altered prompt formats. Across all cases, performance degraded sharply outside familiar training structures.
Their framework, DataAlchemy, showed that models replicate training patterns rather than reason abstractly. Failures could be patched quickly through fine-tuning on small new datasets, but this reinforced the pattern-matching theory.
The paper warns developers against relying on chain-of-thought reasoning for high-stakes domains, emphasising the risks of fluent but flawed rationale. It urges practitioners to implement rigorous out-of-distribution testing and treat fine-tuning as a limited patch.
The researchers argue that applications can remain effective for enterprise use by systematically mapping a model’s boundaries and aligning them with predictable tasks. Targeted fine-tuning then becomes a tool for precision rather than broad generalisation.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
Zimbabwe’s Information and Communication Technology Minister, Tendai Mavetera, revealed the second draft of the National AI Policy during the AI Summit for Africa 2025 in Victoria Falls, hosted by Alpha Media Holdings and AIIA.
Though the policy was not formalised during the summit, Mavetera stated it is expected to be launched by 1 October 2025 at the new Parliament building, with presidential presence anticipated.
The strategy is designed to foster an Africa where AI serves humanity, ensuring connectivity in every village, education access for every child, and opportunity for every young person.
Core features include data sovereignty and secure data storage, with institutions like TelOne expected to host localised solutions, moving away from past practices of storing data abroad.
At least 5 billion people worldwide lack access to justice, a human right enshrined in international law. In many regions, particularly low and middle-income countries, millions face barriers to justice, ranging from their socioeconomic position to the legal system failure. Meanwhile, AI has entered the legal sector at full speed and may offer legitimate solutions to bridge this justice gap.
Through chatbots, automated document review, predictive legal analysis, and AI-enabled translation, AI holds promise to improve efficiency and accessibility. Yet, the rise of AI in legal systems across the globe suggests the digitalisation of our legal systems.
While it may serve as a tool to break down access barriers, AI legal tools could also introduce the automation of bias in our judicial systems, unaccountable decision-making, and act as an accelerant to a widening digital divide. AI is capable of meaningfully expanding equitable justice, but its implementation must safeguard human rights principles.
Improving access to justice
Across the globe, AI legal assistance pilot programmes are underway. The UNHCR piloted an AI agent to improve legal communication barriers in Jordan. AI transcribes, translates, and organises refugee queries. With its help, users can streamline their caseload management, which is key to keeping operations smooth even under financial strain.
NGOs working to increase access to justice, such as Migrasia in Hong Kong, have begun using AI-powered chatbots to triage legal queries from migrant workers, offering 24/7 multilingual legal assistance.
While it is clear that these tools are designed to assist rather than replace human legal experts, they are showing they have the potential to significantly reduce delays by streamlining processes. In the UK, AI transcription tools are being used to provide victims of serious sexual crimes with access to judges’ sentencing remarks and explanations of legal language. This tool enhances transparency for victims, especially those seeking emotional closure.
Even as these programmes are only being piloted, a UNESCO survey found that 44% of judicial workers across 96 countries are currently using AI tools, like ChatGPT, for tasks such as drafting and translating documents. For example, the Morrocan judiciary has already integrated AI technology into its legal system.
AI tools help judges prepare judgments for various cases, as well as streamline legal document preparation. The technology allows for faster document drafting in a multilingual environment. Soon, AI-powered case analysis, based on prior case data, may also provide legal experts with predictive outcomes. AI tools have the opportunity and are already beginning to, break down barriers to justice and ultimately improve the just application of the law.
Risking human rights
While AI-powered legal assistance can provide affordable access, improve outreach to rural or marginalised communities, close linguistic divides, and streamline cases, it also poses a serious risk to human rights. The most prominent concerns surround bias and discrimination, as well as widening the digital divide.
Deploying AI without transparency can lead to algorithmic systems perpetuating systematic inequalities, such as racial or ethnic biases. Meanwhile, the risk of black box decision-making, through the use of AI tools with unexplainable outputs, can make it difficult to challenge legal decisions, undermining due process and the right to a fair trial.
Experts emphasise that the integration of AI into legal systems must focus on supporting human judgment, rather than outright replacing it. Whether AI is biased by its training datasets or simply that it becomes a black box over time, AI usage is in need of foresighted governance and meaningful human oversight.
Image via Pixabay / jessica45
Additionally, AI will greatly impact economic justice, especially for those in low-income or marginalised communities. Legal professionals lack necessary training and skills needed to effectively use AI tools. In many legal systems, lawyers, judges, clerks, and assistants do not feel confident explaining AI outputs or monitoring their use.
However, this lack of education undermines the necessary accountability and transparency needed to integrate AI meaningfully. It may lead to misuse of the technology, such as unverified translations, which can lead to legal errors.
While the use of AI improves efficiency, it may erode public trust when legal actors fail to use it correctly or the technology reflects systematic bias. The judiciary in Texas, US, warned about this concern in an opinion that detailed the fear of integrating opaque systems into the administration of justice. Public trust in the legal system is already eroding in the US, with just over a third of Americans expressing confidence in 2024.
The incorporation of AI into the legal system threatens to derail the public’s faith that is left. Meanwhile, those without access to digital connectivity or literacy education may be further excluded from justice. Many AI tools are developed by for-profit actors, raising questions about justice accessibility in an AI-powered legal system. Furthermore, AI providers will have access to sensitive case data, which poses a risk of misuse and even surveillance.
The policy path forward
As already stated, for AI to be integrated into legal systems and help bridge the justice gap, it must take on the role of assisting to human judges, lawyers, and other legal actors, but it cannot replace them. In order for AI to assist, it must be transparent, accountable, and a supplement to human reason. UNESCO and some regional courts in Eastern Africa advocate for judicial training programmes, thorough guidelines, and toolkits that promote the ethical use of AI.
The focus of legal AI education must be to improve AI literacy and to teach bias awareness, as well as inform users of digital rights. Legal actors must keep pace with the innovation and integration level of AI. They are the core of policy discussions, as they understand existing norms and have firsthand experience of how the technology affects human rights.
Other actors are also at play in this discussion. Taking a multistakeholder approach that centres on existing human rights frameworks, such as the Toronto Declaration, is the path to achieving effective and workable policy. Closing the justice gap by utilising AI hinges on the public’s access to the technology and understanding how it is being used in their legal systems. Solutions working to demystify black box decisions will be key to maintaining and improving public confidence in their legal systems.
The future of justice
AI has the transformative capability to help bridge the justice gap by expanding reach, streamlining operations, and reducing cost. AI has the potential to be a tool for the application of justice and create powerful improvements to inclusion in our legal systems.
However, it also poses the risk of deepening inequalities and decaying public trust. AI integration must be governed by human rights norms of transparency and accountability. Regulation is possible through education and discussion predicated on adherence to ethical frameworks. Now is the time to invest in digital literacy to create legal empowerment, which ensures that AI tools are developed to be contestable and serve as human-centric support.
Image via Pixabay / souandresantana
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
