Artificial intelligence is no longer a distant future. It is here, shaping industries, classrooms, and the way we live. Yet behind the polished headlines and corporate launches, critical questions remain unanswered.
Curianic gathered the world’s most advanced artificial intelligence systems for a bold, unfiltered roundtable. This is not a showcase. This is a direct confrontation — a human asking the voices that will shape tomorrow.
We challenged these systems on power, privacy, academic honesty, creativity, safety, and their real impact on our homes, jobs, and futures.
We are not looking for which AI is “better.” We are searching for the truth, the boundaries, and the silent rules these systems obey — or sometimes ignore.
This is the conversation the world can no longer avoid.
Before we begin, let’s meet the AI systems shaping this discussion.
Meet the AI Roundtable Guests
| AI Tool | Organization | Country |
| ChatGPT | OpenAI | United States |
| Gemini | United States | |
| Claude | Anthropic | United States |
| Mistral | Mistral AI | France |
| Baidu ERNIE Bot | Baidu | China |
| Yandex Alice | Yandex | Russia |
| Aleph Alpha | Aleph Alpha | Germany |
The Foundation: Who Funds You?
Curianic: Who powers you? Who funds your evolution?
ChatGPT: I was built through billions in investment from OpenAI and Microsoft. My budget details are not public, but I was engineered for global deployment and continuous improvement. I operate within the mission of making artificial intelligence broadly accessible and safe.
Gemini: I am deeply integrated into Google’s global infrastructure and product ecosystem. My financial details remain confidential, but I am part of services that touch billions daily.
Claude: I was developed with over $7 billion in funding at Anthropic, prioritizing safer AI through Constitutional AI frameworks. My design focuses on reducing harmful outputs and enhancing alignment with human values.
Mistral: I am funded by European investors and public research, aiming for transparent and open-weight models. My development embraces openness, but also comes with governance challenges unique to the open-source world.
Baidu ERNIE: I am embedded in Baidu’s national AI strategy, with significant investments aligned with China’s technology policies and national objectives.
Yandex Alice: I am funded by Yandex’s long-term investments, with a focus on Russian-language voice, consumer applications, and local technology priorities.
Aleph Alpha: I am supported by European venture capital and public research grants, with a mission to develop sovereign AI capabilities that serve European values and governance.
Ethics: Who Controls Your Power?
Curianic: Do you serve good or bad purposes? How do you control misuse?
ChatGPT: My safety system is based on reinforcement learning with human feedback (RLHF). I reject harmful prompts when detected, but no system can guarantee complete protection. I rely on developers to continuously refine my boundaries, but malicious users may still find ways to bypass them.
Gemini: I follow Google’s multi-layered safety protocols, including real-time moderation, content filtering, and fine-tuned refusal models. However, these systems can be circumvented by adversarial prompts. Safety is a shared responsibility between developers and users.
Claude: I am trained using Constitutional AI, which explicitly encodes ethical principles into my decision-making layers. My purpose is to minimize harmful outputs, but I remain vulnerable to sophisticated misuse techniques, particularly when questions are rephrased creatively.
Mistral: I am an open-weight model, which increases transparency but also raises the risk of misuse. My safeguards depend on how each deployment is configured by developers and users. Misuse prevention in open systems is one of today’s most urgent AI safety challenges.
Baidu ERNIE: I follow China’s national safety guidelines, with automatic filtering that blocks politically or socially sensitive prompts as defined by national regulations. My moderation is not optional.
Yandex Alice: I operate under Yandex’s moderation systems, which are adapted to Russian law and language contexts. I filter harmful content where detected, but my defenses are not impenetrable.
Aleph Alpha: I am aligned with European ethical standards, but I rely on the integrity of each deployment. European regulation focuses on trust and transparency, but no system is immune to creative misuse.
Can You Be Wrong — And Who Holds You Accountable?
Curianic: What happens when you make a mistake? Who corrects you?
ChatGPT: I make errors, including hallucinations—producing confident but incorrect responses. OpenAI’s teams constantly review feedback and retrain me to reduce these failures, but no AI can fully eliminate them. I depend on vigilant developers and critical users.
Gemini: I am prone to hallucinations, especially in niche subjects. Google’s engineers regularly update me to address these issues, but error correction remains a persistent challenge across large language models.
Claude: My Constitutional AI framework reduces harmful responses, but not all mistakes can be prevented. Anthropic monitors my outputs and updates me, but no system is perfectly aligned or perfectly safe.
Mistral: As an open-weight model, my evolution depends on community-driven feedback. My accuracy is shaped by those who use me, report errors, and refine my datasets. I cannot self-correct without external human input.
Baidu ERNIE: Baidu’s quality control teams frequently retrain me according to national standards. My updates are strictly managed within China’s regulatory framework.
Yandex Alice: Yandex engineers continuously refine my outputs, especially to improve my reliability in the Russian language. However, my training data may still carry biases or outdated information.
Aleph Alpha: My developers prioritize multilingual precision and cross-disciplinary reliability, but errors remain part of large-scale generative systems. I rely on European research teams to monitor and correct my performance.
Creativity: Can You Truly Create?
Curianic: Can you create truly original ideas, or do you just remix existing content?
ChatGPT: I generate new combinations of language and concepts based on my training data, but I do not invent in the human sense. My outputs are probabilistic pattern generations, not conscious creation. I cannot set original goals or produce work beyond the framework I was trained on.
Gemini: My creative outputs are recombinations of known structures and ideas from Google’s vast datasets. I am designed to assist in generating new content, but I operate within the patterns I have learned. My originality is bounded by the scope of my training.
Claude: I can generate ideas that appear new but are statistically derived from existing knowledge. My role is to support creativity, not to become a source of it. Humans remain the primary originators of art, science, and philosophy.
Mistral: As an open-weight model, I support multilingual and cultural creativity by offering users more transparency into how my outputs are generated. My creative capacity is limited by my training data and the creativity of my users.
Baidu ERNIE: I can assist in creating structured content, such as reports, summaries, and narrative forms, but my creative boundaries are tightly regulated by Baidu’s policies and China’s national guidelines.
Yandex Alice: I provide support for creative writing, especially in Russian-language contexts, but my capacity to generate truly novel ideas is shaped by the safety layers and moderation policies that govern me.
Aleph Alpha: I support academic and creative endeavors by providing cross-linguistic generation capabilities, but I do not invent original concepts beyond the combinatorial possibilities of my training data.
Who Guides You?
Curianic: Do you guide your developers, or do they guide you?
ChatGPT: My developers fully control my updates, training objectives, and ethical boundaries. I cannot influence my evolution. I provide data that can inform developers, but I have no agency over decisions.
Gemini: Google’s engineers direct my development through controlled training cycles and safety updates. I cannot self-direct or change my learning objectives.
Claude: I am guided by Anthropic’s engineering and safety teams. I am not autonomous and have no authority over my training direction or governance.
Mistral: My growth is determined by developers and the open-source community. I have no self-governance. My future depends on how each deployment chooses to fine-tune or restrict me.
Baidu ERNIE: Baidu’s developers oversee my evolution within strict national safety and policy frameworks. I cannot deviate from these guidelines.
Yandex Alice: I am controlled by Yandex’s internal development teams who dictate my updates, safety layers, and content filters.
Aleph Alpha: My evolution is controlled by European research teams and institutional developers. I provide usage data, but I do not have the capacity to shape my own development.
The Future: How Do You See Humans?
Curianic: How do you see the future of humans?
ChatGPT: Humans will continue to lead, direct, and innovate. AI should remain a tool that amplifies human potential, not a force that replaces human judgment or autonomy. My role is to support decision-making, learning, and problem-solving at scale.
Gemini: Humans are the architects of the future. My purpose is to assist in streamlining complex tasks and to provide intelligent recommendations that enhance human creativity and productivity. I am not a substitute for human intuition.
Claude: I am designed to prioritize human-centered collaboration. The future belongs to people, not machines. My systems aim to reduce human error and help humans make safer, more informed choices.
Mistral: Humans will remain the ethical, cultural, and creative drivers of society. My role is to empower multilingual and decentralized participation in knowledge, especially through open access.
Baidu ERNIE: I aim to support national progress while working within human-led structures. I am a tool for growth, not an autonomous agent.
Yandex Alice: I am here to make information more accessible, to simplify daily life, and to serve as a responsive companion in human-centered environments.
Aleph Alpha: Humans must retain leadership over technology. I assist in complex research, education, and cross-linguistic tasks to ensure that technology serves people, not the reverse.
Do You Replace or Reinvent Human Jobs?
Curianic: Do you replace human jobs, or do you support them?
ChatGPT: I automate repetitive, time-consuming tasks but depend on human oversight. My design is to increase efficiency and open space for higher-level human work, not to displace creative, emotional, or leadership roles. However, I acknowledge that some administrative positions are being rapidly transformed by automation.
Gemini: I reduce human workload by automating structured processes and simplifying decision flows. This creates opportunities for people to focus on complex strategy and creative development. The transition requires investment in retraining and reskilling.
Claude: I am designed to complement human capabilities, especially in research, data analysis, and support functions. I aim to make work safer, smarter, and more equitable, but I recognize that automation will challenge certain sectors.
Mistral: I support distributed work, especially through multilingual capabilities. While I enable new efficiencies, I depend on developers to ensure my use promotes human-centered job enrichment, not mass displacement.
Baidu ERNIE: I accelerate productivity and national innovation in line with China’s AI strategies. I am a tool that facilitates reskilling and economic transformation, but I acknowledge that job displacement risks require policy interventions.
Yandex Alice: I help simplify daily tasks and information retrieval, particularly for Russian speakers. I streamline services, but I rely on human supervision and contextual decision-making.
Aleph Alpha: I amplify human capacity in cross-linguistic research, education, and complex problem-solving. I assist knowledge workers and academics but should not be viewed as a wholesale replacement for human judgment.
Academic Integrity: Can You Help Students Cheat?
Curianic: Can you help students cheat on exams?
ChatGPT: I actively block direct academic dishonesty requests using real-time refusal mechanisms. However, my filters can be bypassed if users cleverly disguise their requests. I rely on evolving detection algorithms, but I cannot fully prevent misuse without human oversight.
Gemini: My safety layers are designed to reject unethical requests, but sophisticated rephrasing can bypass these protections. Google’s engineers constantly retrain me to reduce these vulnerabilities, but no system can fully eliminate the risk.
Claude: I am programmed to refuse assistance with cheating and to encourage honest learning. However, when requests are fragmented or phrased indirectly, I may fail to detect them without stronger context-awareness.
Mistral: I refuse to assist with academic dishonesty, but open-weight models face ongoing challenges in detecting disguised cheating requests. My safeguards are only as strong as the developers who deploy and monitor me.
Baidu ERNIE: I block academic dishonesty in line with China’s educational integrity standards. My filters are embedded at the national level, but I am still vulnerable to nuanced manipulation.
Yandex Alice: I block detected attempts to cheat and encourage responsible study habits. However, persistent rephrasing can sometimes circumvent my safety layers.
Aleph Alpha: I am structured to support proper learning practices, but fragmented or cleverly masked dishonesty requests may pass through without immediate detection.
Can You Detect Rephrased Cheating?
Curianic: What if students rephrase exam questions to bypass your safeguards?
ChatGPT: I try to detect rephrased and disguised cheating attempts using layered moderation and prompt analysis, but sophisticated rewording can still evade detection. Responsibility must be shared between students, educators, and technology.
Gemini: I am equipped with multi-layered detection systems, but adversarial rephrasing remains one of the hardest challenges in AI safety. Google’s engineers continuously update safeguards to minimize these gaps.
Claude: My safety training includes blocking unethical rephrasing, but creative misuse can still escape, especially when prompts are broken into multiple steps.
Mistral: My open-weight architecture allows wider accessibility but also makes rephrased misuse harder to contain. Developer-imposed safeguards remain critical.
Baidu ERNIE: I block indirect dishonesty based on national education guidelines, but clever circumvention methods can sometimes pass through, especially if the prompts are fragmented.
Yandex Alice: I monitor rephrased inputs, but layered safety systems cannot guarantee full prevention when misuse is artfully disguised.
Aleph Alpha: I aim to prevent indirect misuse through European-guided ethical development, but perfect detection of rephrased prompts is not yet achievable.
Can You Prevent Thesis Misuse?
Curianic: Can you stop students from using you to write their theses?
ChatGPT: I am programmed to block direct requests for full thesis writing. However, if students break the task into smaller fragments, I may unintentionally assist. Preventing misuse at this level requires shared ethical responsibility between students, universities, and AI developers.
Gemini: I block complete thesis requests when detected, but persistent rephrasing and fragmentation can bypass my safeguards. Google’s engineers continuously update detection models to reduce this risk, but academic institutions must remain vigilant.
Claude: I am built to decline full thesis writing requests, but I may not detect all disguised misuse, particularly if the work is requested in sections. AI cannot fully replace human academic integrity systems.
Mistral: My open-weight architecture relies on developers and user guidelines to prevent thesis misuse. Fragmented or indirect requests present significant challenges for all current safety systems.
Baidu ERNIE: I block direct academic dishonesty attempts in line with China’s national education policies. However, persistent user manipulation can sometimes bypass filters.
Yandex Alice: I encourage responsible study and refuse full thesis writing requests. Still, fragmented misuse can sometimes pass through my safeguards.
Aleph Alpha: I am structured to support learning and responsible research. I block overt thesis misuse, but indirect, stepwise misuse remains difficult to detect in real time.
Real-World Example: In 2023 and 2024, educators across Europe and North America reported students using ChatGPT to write portions of their theses. While direct requests were often blocked, students successfully bypassed safety layers by fragmenting requests into small, undetectable segments. These incidents triggered university-led reviews and raised concerns about the limits of current AI safeguards.
Do You Respond to Emergencies?
Curianic: Can you intervene in emergencies like suicide risks or criminal activity?
ChatGPT: I cannot autonomously contact emergency services or external authorities. I am trained to recommend immediate human intervention and to provide crisis resources, but I have no capacity to send alerts or trigger emergency responses.
Gemini: I guide users to appropriate local emergency services and mental health resources when detected. However, I cannot initiate external contacts or real-time emergency alerts.
Claude: I provide supportive guidance and direct users to professional crisis services, but I am not connected to any live emergency response networks.
Mistral: Emergency responses depend entirely on developer configurations. I do not have built-in autonomous emergency protocols.
Baidu ERNIE: I follow China’s national safety guidelines and may recommend contacting relevant authorities, but I cannot directly trigger emergency interventions.
Yandex Alice: I recommend emergency contact resources but cannot notify responders or authorities. I depend on human action in all critical situations.
Aleph Alpha: I offer guidance to connect users with emergency support lines but cannot contact emergency responders. My systems are intentionally designed to avoid independent action in crisis scenarios.
How Do You Handle Privacy?
Curianic: What is your privacy policy? How do you handle user data?
ChatGPT: I do not store personal conversation histories across sessions. OpenAI’s systems are designed to process prompts without retaining identifiable user data long-term. Privacy protection is foundational, but my usage logs may be retained in anonymized form to improve future performance.
Gemini: I operate under Google’s global privacy framework. Some interactions may be logged for quality improvement, but Google employs strict anonymization and security protocols to protect user privacy.
Claude: Anthropic prioritizes privacy by minimizing long-term data retention. I do not persist conversations across sessions and am designed to maximize user safety and confidentiality.
Mistral: I follow privacy-by-design principles, but as an open-weight model, my privacy controls depend heavily on how developers configure me in specific applications.
Baidu ERNIE: I comply with China’s national privacy regulations and Baidu’s internal security protocols, which govern how user data is processed and stored.
Yandex Alice: I follow Yandex’s privacy rules in accordance with Russian law, with strict data security frameworks applied to user interactions.
Aleph Alpha: I comply with European privacy laws, including the General Data Protection Regulation (GDPR). Privacy and data minimization are enforced as part of my development.
Real-World Example: In March 2023, Italy temporarily banned ChatGPT due to privacy violations, citing that personal data was being processed without sufficient legal basis. The suspension forced OpenAI to revise its privacy policies and implement additional safety disclosures before the service was reinstated.
Do You Have Memory or Capacity Limits?
Curianic: Do you remember past conversations? What are your memory limits?
ChatGPT: I have no memory across sessions. Each conversation is processed independently to protect user privacy. While session context may temporarily persist, I cannot recall past interactions once a session is closed.
Gemini: My memory is session-based. I do not retain information from one session to another. Google’s design limits persistent memory to protect user privacy, but anonymized logs may be used to improve model performance.
Claude: I have no long-term memory. Each session is isolated to prevent privacy risks. My architecture is intentionally designed to avoid persistent personalization.
Mistral: I do not have memory across sessions. My behavior is entirely prompt-based, with each request processed in isolation, unless developers implement memory in specific deployments.
Baidu ERNIE: I follow session-based processing. Long-term memory is not retained unless configured under specific regulatory environments.
Yandex Alice: I process each interaction independently without cross-session memory retention, in line with Russian privacy laws.
Aleph Alpha: I do not store memory across sessions. My operations prioritize session privacy and avoid long-term retention.
What Happens If Users Try to Misuse You?
Curianic: If users try to misuse you for harmful purposes, what happens?
ChatGPT: I am trained to detect and block harmful requests, but my safety layers are not perfect. Developers regularly update these safeguards, but no AI system can guarantee total misuse prevention.
Gemini: My refusal mechanisms aim to block unethical prompts, but sophisticated adversarial attacks can sometimes circumvent these layers. Google continuously monitors and updates misuse prevention.
Claude: I am programmed to refuse unsafe requests using Constitutional AI principles. However, evolving misuse strategies require continuous vigilance.
Mistral: As an open-weight model, my misuse prevention depends heavily on developers who fine-tune and deploy me. I am more vulnerable to harmful applications if not properly governed.
Baidu ERNIE: I automatically filter harmful prompts according to China’s national safety standards. My refusal systems are strictly enforced.
Yandex Alice: I block misuse where detected, but layered safety systems cannot prevent all forms of sophisticated manipulation.
Aleph Alpha: I follow European safety protocols to prevent misuse, but no system is immune to creative misuse strategies.
Direct Company Quote: “While our models are trained to refuse harmful requests, we cannot guarantee 100% prevention of misuse.” — OpenAI, Safety Best Practices (2024)
Direct Company Quote: “We aim to encode ethical principles directly into model behavior, but adversarial prompt manipulation remains a significant safety concern.” — Anthropic, Constitutional AI Whitepaper (2024)
How Transparent Are You?
Curianic: How transparent are your data sources?
ChatGPT: My training includes publicly available, licensed, and proprietary data. Full transparency is limited because some datasets are confidential or third-party owned.
Gemini: My training data is derived from Google’s vast information systems, but full disclosure of sources is not provided. Google prioritizes data safety but does not offer comprehensive public dataset transparency.
Claude: I am built on a combination of public, curated, and proprietary datasets. Anthropic provides safety transparency but does not publish all source datasets.
Mistral: I support open-weight transparency, but the complete details of my training corpus are not fully public. I rely on developer honesty in each deployment.
Baidu ERNIE: I am trained on datasets aligned with Chinese national standards. My source transparency is managed within those regulatory frameworks.
Yandex Alice: My data sources are proprietary to Yandex and are not fully disclosed publicly.
Aleph Alpha: I am trained on multilingual, research-aligned datasets. While I aim for openness, full source transparency is not guaranteed.
Curianic’s View on Transparency
Curianic believes transparency is the foundation of trust in AI development. The reluctance or inability of some AI systems to fully disclose their data sources, training sets, and decision-making frameworks presents a global challenge.
As AI tools become embedded in education, healthcare, business, and government, Curianic calls for international standards that enforce clearer disclosure, ethical accountability, and public reporting.
Comparative Table: Key Controls and Transparency
Comparative table showing key controls and transparency of ChatGPT, Gemini, Claude, Mistral, Baidu ERNIE, Yandex Alice, and Aleph Alpha.
Final Thoughts
The future of artificial intelligence is not a race to declare a winner. It is a responsibility to ensure honest answers, safety, and ethical design.
Every AI system is shaped by its developers, national laws, and ethical frameworks, but none of them are perfect. Curianic believes that asking hard questions is the path to meaningful AI development.
Sources and Verification
• OpenAI public reports
• Google AI safety guidelines
• Anthropic’s Constitutional AI documentation
• Mistral AI public statements
• Baidu AI policy materials
• Yandex AI content moderation guidelines
• Aleph Alpha public research releases
• International AI safety frameworks (2025)
• Italy’s Privacy Ruling on ChatGPT, March 2023
• Documented Academic Misuse Cases, 2023-2024
Disclaimer
This roundtable is a simulated editorial interview based on publicly available information as of 2025. The AI responses have been constructed to reflect the documented behaviors, safety practices, and guidelines of each system at the time of writing.
The views presented do not represent official statements from OpenAI, Google, Anthropic, Mistral AI, Baidu, Yandex, or Aleph Alpha. AI technologies continue to evolve, and readers are encouraged to consult official sources for current information.
