Imagine you have used a generative artificial intelligence (AI) tool such as ChatGPT to tidy up notes you took while in a meeting. Your colleague comments on how clear they are. You don’t disclose it was the AI that made the notes clear and not you.

Now consider a different scenario. You are at your mother’s funeral. Her best friend of many years delivers a heartfelt eulogy, wishing her well in the afterlife. But later you discover her friend did not actually write the eulogy in any way – AI did.

The undisclosed use of generative AI in these two scenarios is deceptive. But is it morally wrong?

It’s worth considering this philosophical question in detail, given the rapid uptake of generative AI and the fact research has found people may be strongly incentivised to not disclose their use of generative AI because it may impact their relationships.

This is because people take generative AI outputs, generally, to be less valuable, and regard those who use the technology as less competent and authentic.

Distinguishing different kinds of deception

Roughly speaking, if you’re engaging in a “deceptive act”, you’re trying to get someone to believe something you know is false. However, deception can come in different varieties.

Philosopher John Danaher provides a useful framework to distinguish between three forms of deception by AI or robots. This framework is useful because, just as robots might convincingly mimic human behaviours, generative AI technologies are allowing humans to do the same.

Some deceptions involve lying or misrepresenting the external world, such as telling someone you saw a horse in the street, even though you didn’t. Danaher calls these “external state” deceptions.

Other deceptions involve lying or misrepresenting facts about ourselves, such as making someone believe you’re an accomplished artist, even though the artwork you showed them was generated by AI. Danaher calls these “superficial state” deceptions.

We can also deceive others into believing we lack thoughts, feelings or competencies we actually possess, such as pretending to not understand a language we speak in order to eavesdrop. Danaher calls these “hidden state” deceptions.

So, when is deception immoral?

To go back to the first example, by not disclosing you used AI to tidy up meeting notes, you’ve allowed your colleague to believe you have the capacity to do the work, which might be true. However, you also allowed your colleague to believe that you demonstrated that capacity by doing the work, which is false. This would fall into the category of an “external state deception”.

While this deception is morally objectionable, it’s arguably ethically permissible. Trivial deceptions like this happen all the time – and surely we aren’t obligated to always disclose everything about what we do and why we do it.

For example, we don’t blink an eye at undisclosed use of spell-checking software because, in most situations, being a good speller isn’t important. But triviality depends on context. If someone used spell-checking software at a spelling bee, we might be less forgiving.

The scenario about the funeral speech is similar to the first scenario, but less trivial. Your belief over your mother’s friend’s superficial state – that they wish her well – may or may not be false. However, your belief over the external state of affairs – that the eulogy is a demonstration of those well-wishes – is certainly false.

This is more morally problematic. When we claim an AI-generated output as our own – and particularly one that aims to reflect something about ourselves – we signal to others that we not only endorse the output, but that we have authored it. In this case it matters to us that the friend is the source of the eulogy – and not AI. The external state deception is deceptive in a non-trival way.

We imply the output was directly caused by our thoughts, feelings or competencies. When we don’t disclose our use of AI, we deprive others of the kinds of information needed to form true beliefs about how the world is and how others are. This is wrong if people deserve to have such information.

However, the eulogy example can still show how not disclosing our use of AI can – all things considered – sometimes be permissible. Perhaps, for example, the friend was so wracked with grief, that having AI write the eulogy on their behalf was the only way for them to get the speech written in time for the funeral. So they endorsed the generated output as their own.

In such cases, not disclosing the use of AI may be permissible, even though still a morally objectionable kind of deception. This is because, like triviality in the first scenario, other reasons might sufficiently outweigh the wrongness of non-disclosure.

Using AI more ethically

So, how can people use generative AI more ethically?

If we are to avoid immorally deceiving others, we ought to disclose our use of it in non-trivial cases.

What makes undisclosed AI use non-trivial is malleable and context-dependent. It changes in response to social norms couched within particular social practices.

Being open about AI use gives others the opportunity to form more accurate beliefs about what we are communicating – and the internal states our communication demonstrates.

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Initially, time spent with AI agents may displace time interacting with real humans. Fewer opportunities to build these skills could lead to a reduced capacity to maintain caring human relationships. Difficulties in maintaining human relationships may promote a preference of machine over human relationships as children expect “frictionless” interactions.

And the risks may compound over time.

Increased trust leads to increased use and engagement with the toys. Recent estimates suggest close to 80% of children aged 10 to 17 have used an AI companion or assistant, so it’s urgent children and young people be taught how to “reality check” their AI “buddies”.

The ability to read and write was once a requirement to use most online tools and services. This literacy barrier no longer exists today with many generative AI toys, tools and devices now widely accessible to younger children through voice interactions.

Sounding human

Eventually, these developments may lead to less satisfying human connections, increasing loneliness, which in turn promotes increased time spent with AI.

Last year, for example, Mattel, one of the world’s biggest toy makers, announced a strategic collaboration with OpenAI to support AI-powered products.

This is a feature of many AI toys.

Research shows young children are particularly prone to developing a strong sense of emotional attachment to conversational AI agents.

Importantly, the risk factors in AI toy design, such as the degree to which they pretend to be human, can be changed by manufacturers, offering opportunities to follow safety-by-design.

Infinite chat

ChattyBear, a soft, brown-furred teddy bear, begins every conversation with a jubilant, “Hello, my buddy!”

These high tech toys are powered by generative AI engines such as ChatGPT and are now widely available online. They are being marketed as a way to give children as young as three an educational advantage and a new type of play – without the perils of screen time.

Research has also found some AI toys discuss very adult topics – such as sexual fetishes and how to find knives and start fires.

But enabling endless conversations, or infinite chat, poses risks when it comes to children learning how to moderate their technology use.
In the social media realm, the infinite scroll of TikTok or Instagram is seen as a potential challenge to teens limiting their use to healthy amounts.

Marketing material for ChattyBear says the toy offers “safe, filtered content for children”. The Conversation contacted the manufacturer for further detail about this but did not receive a response before deadline.

For younger children especially, understanding that their teddy or toy isn’t “alive” or magic can be hard. This is especially true if “teddy” uses language that positions it as a trusted friend – for example, by insisting it is a “real buddy”.

No longer the province of the imagination, ChattyBear is part of a new generation of artificial intelligence (AI) toys. It can tell stories, chat about a child’s interests, play games or even discuss what’s happening in the world today.

Children’s wellbeing

Right now, playing with AI toys under the supervision of a parent or trusted adult may well be a fun way to explore the world of AI together. But especially for younger children, playing with AI toys without supervision opens the door to a wide range of new risks.

The novelty of AI toys means there is little evidence to confirm these possible detrimental impacts. Further research is needed – especially as the AI toy industry is set to grow even more.

Sharing personal details with a friendly bear might feel safe. But that chat could be training data for the next large language model.

However, the business models behind many AI toys capitalise on the duration and intensity of users’ engagement, leaving little incentive for companies to change their products.

Infinite chat also opens the door to infinite data collection.

The potentially intimate nature of conversations with AI toys might lead children to presume their conversations are private. But most AI terms of use reveal the opposite to be true.

After evaluating six different AI teddy bears and toys over several months, it’s clear how these toys could feel compelling for children. Yet as our new report highlights, there are new risks that come with AI toys turning up in young children’s lives.

Barriers to the online world are gone

Children’s rights advocates have raised concerns that excessive engagement with AI agents may reduce opportunities for children to develop these skills.

Childhood is a critical period when young people develop the social and emotional skills to form and maintain trusting relationships. These skills are usually learned through interactions with trusted friends and adults.

The audio turn opens up new technological play, experiences and opportunities for children. But it also means adults need to ensure AI toys can be safe for younger children, too.

Sounding human builds an artificial sense of trust and intimacy, which can be especially problematic for children when combined with sycophantic language choices – or excessively agreeable, validating and even flattering language.

The marketing materials for many AI toys often highlight “endless conversations” as a feature of these devices.

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Two recent industry reports validate CrowdStrike’s leadership in the identity threat detection and response (ITDR) market: 

• Frost & Sullivan has named CrowdStrike its 2026 Company of the Year for Identity Threat Detection and Response
• GigaOm has positioned CrowdStrike as a Leader and Fast Mover in the 2026 GigaOm Radar for Identity Threat Detection and Response

Identity is the front line of modern cyberattacks. Today’s adversaries log in and use legitimate identities to move laterally, escalate privileges, and operate inside legitimate sessions as trusted users. They are moving fast — the fastest eCrime breakout time recorded in 2025 was 27 seconds — and they’re gaining an advantage over security teams who can’t keep pace.

The requirements for identity security have changed, fueled by AI agents transforming business processes and operating with machine speed and elevated privileges. Identity risk has become continuous, yet traditional identity tools still rely on static access and fragmented controls. Organizations relying on these legacy models struggle to correlate risk in real time or stop attacks before they escalate. 

ITDR has rapidly become a critical security layer as the market shifts toward a continuous identity model that detects threats and continuously verifies and enforces access in real time. CrowdStrike Falcon® Next-Gen Identity Security advances the market beyond static access controls and gives agentic enterprises the protection they need.

These recognitions signal that the ITDR market is converging. CrowdStrike is defining where it’s going.

Frost & Sullivan: Validating a Unified, Continuous Identity Model

Frost & Sullivan’s recognition of CrowdStrike as Company of the Year for ITDR highlights how identity security must be delivered as a unified, continuous, real-time control system.

“CrowdStrike’s unified, cloud native platform that delivers end-to-end identity visibility, just-in-time privileges, behavioral analytics, and automated response across human and non-human identities enables a significant competitive advantage,” Frost & Sullivan states in its write-up. 

The analysis emphasizes CrowdStrike’s ability to deliver:

• Continuous, real-time visibility across human, non-human, and AI identities
• Behavioral, context-driven detection 
• Zero standing privileges through needs-based, context-aware access
• Automated response and remediation at machine speed

The result is full end-to-end identity security. With CrowdStrike Falcon® Fusion SOAR workflows, customers can automatically reset compromised passwords, remediate risky accounts in batches, and enforce conditional access or privilege controls based on real-time risk scores. Customers gain real-time visibility into AI and SaaS agents, including permissions, data access, and activity, and can monitor how these identities interact with sensitive systems and datasets over time.

Frost & Sullivan emphasizes the benefits of CrowdStrike’s platform approach. Falcon Next-Gen Identity Security is delivered from the unified CrowdStrike Falcon® platform, which is built on a cloud-native architecture that treats identity as a first-class security signal alongside endpoint and cloud data. Because its capabilities are delivered through one platform, organizations can avoid the complexity of integrating multiple tools and operationalize ITDR best practices in days. 

The impact of the Falcon platform is quick and measurable. Frost & Sullivan highlights a real-world deployment of Falcon Next-Gen Identity Security in which an organization immediately discovered 45,000 unused accounts, 2,500 compromised passwords, 42,000 stealth admin accounts, and 48,000 accounts with privileged escalation paths, which collectively represent massive standing risk.

“By consolidating fragmented tools, reducing operational complexity, and providing high fidelity detections with machine speed response, CrowdStrike delivers superior price/performance value and a consistently strong customer experience,” Frost & Sullivan says.

GigaOm: Leadership Defined by Execution and Momentum

While Frost & Sullivan validates CrowdStrike’s model, GigaOm highlights our execution. CrowdStrike’s recognition as a Leader and Fast Mover in the 2026 GigaOm Radar for Identity Threat Detection and Response reinforces our market leadership and innovation velocity.

CrowdStrike achieved high scoring in Key Features with 4.6/5, Emerging Features with 4.3, and Business Criteria with 4.7. GigaOm’s analysis highlights several key strengths including:

Non-Human Identity Security 

Identity threats are evolving as organizations adopt more SaaS applications and autonomous AI agents, each of which is backed by human and non-human identities with persistent access to systems, applications, and sensitive data.

CrowdStrike secures every identity type across every environment, with comprehensive non-human identity discovery across cloud, on-premises, AI agent platform, and SaaS. It shares context including linked accounts, privileges, and cloud resource access; detects anomalies and behavioral deviations; and provides risk scoring for non-human identities. The outcome is full protection across the modern identity attack surface.

AI-Enhanced SecOps 

CrowdStrike operationalizes AI as a core part of detection and response. CrowdStrike® Charlotte AI™ performs agentic triage and investigation, while Falcon Fusion SOAR automates response. 

As stated in the GigaOm report: “CrowdStrike’s Charlotte AI is a deeply integrated AI copilot with agentic capabilities powered by generative AI and specialized agents. It supports natural language queries across Falcon data, automated detection triage, priority and confidence scoring, and step-by-step response guidance.”

Charlotte AI supports advanced automation through tight integration with Falcon Fusion SOAR, which is also natively integrated into the Falcon platform and provides a no-code automation and orchestration engine that enables teams to automate end-to-end response workflows. Falcon Fusion SOAR offers over 1,500 automated actions, including first-party and third-party actions that can be executed either via CrowdStrike or through integrations with other tools.

The Future of ITDR Is Continuous Identity

Across both reports, a clear pattern emerges. The top priority for identity security is continuously securing access. Organizations must continuously verify access, evaluate risk using real-time signals, dynamically adjust and revoke privileges, and immediately connect detection and enforcement.

These recognitions reflect where the market is going. CrowdStrike’s advantage is the Falcon platform was built for this shift. It already unifies identity, endpoint, cloud, and SaaS security and enriches it with real-time telemetry, threat intelligence, and AI. As identity security becomes a continuous control system, CrowdStrike is the best-equipped to drive the market forward. 

Additional Resources

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