In a world where relationships have become more explicit and more complex, a curious psychological phenomenon has been quietly gaining attention – gamophobia, the fear of commitment or marriage.It’s sometimes more than just cold feet, nervousness before a proposal, or hesitation about settling down. Gamophobia is a deeply rooted, lived experience that can color every relationship, shape life choices, and define what love looks like for many individuals. Increasingly, mental health professionals, authors, and even everyday couples are referring to this concept not just as a fancy term, but as a real emotional resistance.27 year old IT professional Ankur Halder has it right – Like Abhay Deol I say Life No will meet again“I don’t want two bodies and one life.” The word “gamophobia” comes from the Greek gamos (marriage) and phobia (fear). At its core, it talks about the fear of getting married or entering into a long-term intimate commitment. Yet, in practice, it is far more subtle. People who struggle with gamophobia are not necessarily afraid of love or companionship. Instead, they fear the permanence, vulnerability, expectations, and potential loss of autonomy that may result from lifelong attachment.But why has this fear become more visible now? Why are more people willing to call themselves “afraid of commitment”? Is this merely a symptom of a generation without choices, or are its roots rooted in deeper psychological and social changes? And importantly – what does this look like in a place like India, where marriage still holds cultural solemnity, unlike many parts of the world?To explore these questions, we must go beyond the labels and into the lived realities that echo homophobia in the twenty-first century.

The Many Faces of Gamophobia

Gamophobia is not a clinical diagnosis in major psychiatric manuals such as the DSM-V; It is a loosely defined term used in the psychological, cultural, and pop-psychology fields. Nevertheless, its emergence reflects real emotional and relational patterns that therapists see every day.For some people, this manifests as anxiety or nervousness when conversations about the future become serious. For others, it shows up as long-term sabotage in the relationship – starting off strong, pulling away, or falling into a self-indulgent breakup before things even get real. Some people experience insomnia, avoidance, or physical symptoms at the thought of connecting their lives with another.Importantly, gamophobia is not just about the fear of marriage. This can be expressed as:

For a growing number of young Indians, this fear is not abstract. It unfolds at a very specific moment – ​​when romance begins to take hold.

Relationships in this country rarely hang out in emotional limbo. They are expected to finish. They have to be formalized. They should move towards marriage.And often at this very threshold some change occurs.

Aarav, 32, who works in an MNC in Mumbai, said he has been in three serious relationships in the last decade. Each followed a similar rhythm: an intense beginning, emotional intimacy, shared holidays. For months, sometimes years, everything seemed certain.Then there were talks of meeting the parents. About the deadline. About “where is this going”, and began to back off.“I don’t know what happens,” he says. “It’s like something goes off. I start imagining all the ways it could go wrong. What if I lose my freedom? What if I’m not ready? What if I choose wrong and can’t undo it?”Gamophobia often manifests in this way. Individuals easily form romantic bonds. They are affectionate, attentive, emotionally connected. But as a relationship approaches formal commitment – ​​engagement, marriage, shared finances – the anxiety increases. The future stops feeling romantic and begins to seem irreversible.

does not equal the inability to love

One of the most persistent myths about gamophobia is that it indicates emotional immaturity or an inability to feel deeply. This notion couldn’t be further from the truth.People who struggle with commitment anxiety often fall deeply in love. They can be attentive partners, emotionally available in the present, and truly invested in their relationships. The difficulty is not in affection. It lies in anticipation.For some people, fear is rooted in childhood experiences. For others, it stems from witnessing marital dissatisfaction. And for many in contemporary India, it arises from the burden of making the “right” decision in a world that offers both endless choices and irreversible outcomes.In that sense, gametophobia is less about rejecting love and more about fearing a mistake that can’t be undone.A 29-year-old woman (choosing to remain anonymous) grew up watching her parents argue behind closed doors while maintaining a public image. Divorce was never discussed. Silence was easier than separation.“When people talk about marriage,” she says, “I don’t imagine romance. I imagine staying even when you’re unhappy.”Children absorb much more than they understand. When marriage is viewed as a matter of endurance rather than companionship, commitment begins to subconsciously resemble prison.

Why is the fear of commitment increasing?

culture of choice and comparison

We live in an age where the options, especially romantic options, seem endless. Dating apps, social media, global mobility, and curated images of the “perfect relationship” create the illusion of infinite possibility. When one believes the next swipe may be better, commitment to one person can paradoxically feel limiting rather than reassuring.This reflects deep cognitive patterns of comparison, fear of missing out, and an abundance of choice. Instead of limiting options that feel comfortable, this can create anxiety about losing out on potential options forever.

individual identity over collectivity

In recent decades, individualism has become central to people’s sense of self. Career goals, personal development and self-discovery are given more priority than ever. Although this is empowering, it also changes the way we view relationships. Commitment begins to feel like a trade-off – balancing autonomy with attachment. Ankur Halder said, “I believe that a healthy relationship should be two independent individuals living together. Relationships today have evolved, unlike older generations like my grandparents, where partners were often highly dependent on each other. I appreciate that relationships now allow for more individuality.”

witness to the breakdown of relationships

We grow up surrounded by stories of failed marriages, divorces and high-profile celebrity breakups. Watching relationships break down shapes our views about commitment – ​​making it seem risky rather than romantic.

Trauma and Attachment Styles

How we connect emotionally is influenced by early life experiences. People with avoidant attachment often fear losing independence in close relationships. People with anxious attachment may fear abandonment even in healthy partnerships. Someone who has had an initial friendship end suddenly may struggle to fully commit to their partner, worried that closeness will lead to inevitable loss.

Changing gender roles and expectations

Traditional roles, such as men as sole breadwinners and women as primary caregivers, have changed, but old expectations don’t disappear overnight. Women do not want to be tied down to domestic duties, and years of social conditioning have made many feel that, at some point, they will have to sacrifice their dreams to meet relationship expectations. People everywhere often find themselves balancing new possibilities with inherited norms, creating tension in romantic relationships as they decide who does what, how decisions are made, and what each partner should contribute.

Gamophobia in India: Between tradition and modernity

In India, marriage has long been considered a central life milestone – expected, celebrated, and often organized by the family. Urbanization, increasing female workforce participation and exposure to global culture have changed the way young Indians think about partnerships. Emotional well-being and personal growth matter more than ever.At the same time, entrenched expectations also persist:

In this environment, gametophobia can take unique forms. For some people, it becomes a resistance against pressure, a boundary against social pressure. For others, it reflects genuine uncertainty about whether traditional marital structures align with their evolving identity.Adding another layer of complexity, leaving a partner in India is often socially difficult. Relationships aren’t just between two individuals – they involve familial expectations, societal judgments and, in many cases, children. In India, many people hesitate to end a relationship for fear of the stigma of separation or the impact on their children, even if they feel unfulfilled. This has led to a common misconception: persisting despite unhappiness is often interpreted as evidence of commitment or love, when instead it may reflect social pressures and obligations.

Intergenerational values ​​also play a role. Many Indian families value patience and sacrifice in relationships. While admirable, these ideals may inadvertently silence emotional needs. Young adults may find themselves torn between honoring tradition and honoring their own urgency.Mental health awareness is still developing in India. Anxiety over commitment may be dismissed as stubbornness or irresponsibility rather than understood as an emotional complex. Without language for their fears, many individuals internalize the guilt instead of seeking support.

Not all fears are pathology

It is important to recognize that gametophobia is not always dysfunctional. Fear can be protective, especially after painful or unstable relationships. This may indicate a need for clarity, healing, or strong identity building.In a society that often equates marriage with success, it’s not necessary to pause or question. This may be wisdom.Challenging traditional marriage norms, Ankur said, “My view about marriage is somewhat skeptical. While I understand that this works well for many people, I have noticed that most marriages seem complicated and full of ongoing issues. This has forced me to question whether the institution itself is necessary, or whether commitment can exist in other forms.Gamophobia is a mirror. It reflects personal insecurities and broader cultural change. It reminds us that commitment is not just a social contract, but an emotional decision shaped by history, identity, and context.The growing visibility of commitment anxiety in India and beyond doesn’t mean a generation is incapable of love. This shows that people are thinking more deeply about the demands of love.And perhaps, in asking those difficult questions, we are not walking away from commitment but learning to approach it with greater awareness.After all, love is not weakened by contemplation.It is strengthened by selection.

Security primarily focuses on preventing direct harm from an AI system through internal technical controls and safeguards. It asks: Does the model make accurate predictions? Does it resist adversarial attacks? Are data and infrastructure secure from external threats? Security is largely an intrinsic property, which can be measured through controlled test environments and technical benchmarks.

In contrast, trust is a more inclusive concept that encompasses fairness, explainability, privacy, robustness, governance, and social impact across the board.

A system may be technically secure yet be highly unreliable, and conversely, internal security verification provides minimal assurance to external stakeholders.

The same dimensions of AI design – explainability, performance, fairness, privacy, and robustness – are understood and implemented completely differently depending on whether the overarching goal is security or trust.

Whereas, in the belief model, explanations serve a fundamentally different purpose. They enable end-users and domain experts to understand decisions in their own conceptual language and verify the logic against their expertise.

For example, a medical diagnostic model designed for security can explain itself to engineers through feature importance scores and attention maps.

The same model designed for confidence will explain to physicians using clinical language, highlighting which symptoms and test results contributed to the diagnosis that physicians can verify against their medical knowledge. These are not identical interpretations as they reflect different audiences and different purposes.

These are engineering questions answered through controlled benchmarking.

However, trust requires external validation and verifiable proof.

To make AI trustworthy, it demands third-party verification: independent auditors, preferably with access to proprietary models through privacy-preserving mechanisms such as trusted execution environments, that certify performance and bias characteristics.

The EU AI Act and the emerging regulatory framework clearly require this distinction.

This leads to designs that exclude sensitive characteristics or enforce “fairness through anonymity” – the assumption that removing demographic data will prevent discriminatory outcomes.

This approach repeatedly fails because algorithms may detect proxy variables that encode protected characteristics – a gender-blind credit scoring system could discriminate against women if the model finds that certain phone types or app choices are related to female identity, even if gender is excluded from the input.

The algorithm’s optimization objective – predicting loan default – is agnostic to the developer’s intentions; If the training data contains historical gender bias, the model will find shortcuts to that pattern. Trust-oriented fairness addresses this by continuously auditing across demographic groups, testing for both direct and indirect discrimination, and confirming that performance generalizes equally.

Trust-oriented privacy centers on user agency and informed consent: Do users know what data is being collected and why? How is it used? Can they access, correct or delete their information? Do they have any meaningful choice about what is stored?

Privacy by design in the trust paradigm means minimizing data collection, obtaining explicit consent for each use, implementing transparent data-handling practices, and respecting user rights regardless of technical feasibility.

Confidence-oriented robustness asks whether the system generalizes reliably across real-world situations and diverse populations.

A diagnostic AI system may be trained robustly against adversarial examples, but it silently fails when deployed in a different hospital with different patient demographics, equipment, or clinical workflows.

Recent research clearly shows this difference: models adversarially trained to be robust against one type of perturbation (for example, specific image distortions) often become less robust against other, unexpected perturbations.

Trust defines ethics as relational integrity: Is the system really fair to all the groups it affects? Do stakeholders feel that their values ​​are respected? Is responsibility clear when the system causes harm? Does the governance reflect the interests of affected parties, not just developers?

This requires ongoing engagement with diverse stakeholders, monitoring of real-world impacts, and adapting governance as ethical issues arise.

Algorithms designed for hiring may claim ethical compliance by documenting bias-mitigation techniques and internal fairness audits.

It earns trust by demonstrating that hiring outcomes are consistent across demographics, that candidates understand how they are evaluated, that recruiters maintain meaningful human judgments, and that the company adjusts the system based on feedback about fairness concerns.

Designing AI for security focuses on preventing exploitation and system failure through rigorous internal testing, adversarial robustness and threat modeling, strong security controls (access management, encryption, monitoring), disciplined technical documentation of specifications and risks, and penetration testing.

On the other hand, designing for trust moves forward by ensuring that the system credibly meets stakeholders’ needs in context, which requires involving stakeholders throughout the lifecycle, building transparency into the process (auditability, model provenance and training-data documentation), providing friendly interpretation to multiple audiences (end-users, domain experts, regulators), externally validating performance through third-party review, maintaining meaningful human oversight rather than box-ticking, supporting diverse populations. And situations include monitoring real-world outcomes and maintaining governance. Feedback loops that adapt when there is evidence of ethical or performance issues.

Current regulatory frameworks are increasingly recognizing this gap.

The EU AI Act classifies certain applications as “high risk” and calls for extensive documentation, external auditing and transparency for those systems because security alone is insufficient.

NIST’s AI risk management framework explicitly addresses multiple dimensions of reliability, not just security or accuracy.

Emerging standards, such as the ISO/IEC framework, are developing criteria for verifiable reliability based on objectivity, interpretability, and robustness.

As AI becomes increasingly involved in decision making that affects millions of people, the difference has become fundamental, not just academic. Organizations that recognize and invest in differences are more likely to create systems worthy of genuine trust.

Security is an essential foundation. There is no doubt about it. But trust is a broader social and relational asset. After all, no one wants to trust a system they know is insecure or unreliable.

–

(Views expressed are personal)

About the author: Professor Balaraman Raveendran heads the Department of Data Science and Artificial Intelligence (DSAI), Wadhwani School of Data Science and Artificial Intelligence (WSAI), Robert Bosch Center for Data Science and Artificial Intelligence (RBCDSAI) and Center for Responsible AI (CeRAI) at IIT Madras. His research interests focus on learning from and through interactions and span the areas of geometric deep learning and reinforcement learning. Additionally, he is associated with the Center for Responsible AI (CERAI), where his work aims to promote the responsible development and deployment of AI technologies across various domains, as well as ensuring that they are transparent, fair, and aligned with social values.