Hi Friends,

Even as I launch this today ( my 80th Birthday ), I realize that there is yet so much to say and do. There is just no time to look back, no time to wonder,"Will anyone read these pages?"

With regards,
Hemen Parekh
27 June 2013

Now as I approach my 90th birthday ( 27 June 2023 ) , I invite you to visit my Digital Avatar ( www.hemenparekh.ai ) – and continue chatting with me , even when I am no more here physically

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Tuesday, 26 May 2026

Solar vs Coal: 300 GWh Lost

Solar vs Coal: 300 GWh Lost

I write this as someone who has watched the rise of solar with both exhilaration and unease. The headline is stark: in Q1 2026, roughly 300 GWh of clean solar generation went unused — curtailed or otherwise wasted — because it could not be absorbed by the grid or market. That is 300,000 MWh of zero-marginal-cost electricity that never reached a socket. To put it in human terms, at an average household consumption of ~300 kWh/month, this is roughly equivalent to supplying one million households with a month of electricity. That lost opportunity deserves a clear accounting: what happened, why it happened, what it means, and what we must do next.

What happened — figures and timeline

  • Time window: Q1 2026 (January–March). The system operator reported cumulative curtailment of about 300 GWh of solar during this quarter, concentrated around several high-solar, low-demand days and during limited system-transfer windows.
  • Pattern: large midday spikes in solar output — particularly on clear, low-demand weekends — coincided with transmission bottlenecks and limited short-term market options. Curtailment events clustered in late January and mid-February when new utility-scale projects came online in the same export corridors.

I have been tracking the same structural issues for years — especially transmission and access constraints that blunt the value of utility-scale solar Solar Power : GigaWatt or GigaFlop ? — and the events of Q1 2026 are an ugly confirmation of those risks.

Root causes

Multiple failures combined to turn abundant sunshine into wasted electrons:

  • Grid constraints: limited transmission capacity and congested corridors prevented export of midday solar to distant load centers. This is the recurring culprit I flagged earlier — inadequate transfer capability and planning mismatch between generation build-out and network upgrades Transmission Capacity is the Culprit !.

  • Market rules and settlement design: inflexible day-ahead markets, punitive imbalance charges, and slow intraday trading meant operators defaulted to curtailment instead of redispatching or using price signals to shift demand.

  • Storage shortage: insufficient utility-scale batteries and limited behind-the-meter storage meant there was nowhere to park excess midday generation for later consumption.

  • Forecasting and operational coordination errors: inaccurate short-term solar forecasts and weak coordination between regional system operators increased uncertainty and raised the perceived risk of overgeneration.

Impacts — immediate and ripple effects

  • Emissions: every MWh of curtailed solar that the system replaced by burning coal or keeping coal online implies additional CO2 emissions compared with the zero-carbon alternative. Using a conservative coal-intensity range (~0.8–1.0 tCO2/MWh), the 300 GWh lost represents roughly 240,000–300,000 tonnes of CO2 of foregone abatement in that quarter alone.

  • Economics: curtailment destroys developer revenue and raises the levelized cost of new projects. With no reliable offtake, investment risk increases and financing costs rise.

  • Solar developers: developers face lost energy sales and strained PPA relationships; some will have to renegotiate contracts or accept compensation shortfalls.

  • Coal plants: paradoxically, coal units receive mixed impacts. Some benefit from reduced ramping and capacity payments, while others incur inefficient cycling costs and poorer plant economics as they are forced into stop-start operation.

Policy and technical fixes (what actually works)

We can — and should — move quickly on several fronts. These are practical, not merely aspirational.

  • Market design changes

  • Create faster intraday markets and shorter settlement windows so excess solar can be traded or priced down, avoiding blunt curtailment.

  • Reform imbalance and settlement rules so generators are not perverse-incentivized to shut down renewables when grid stress appears.

  • Introduce locational pricing or congestion signals so market participants see the true value of moving energy and investing in constrained corridors.

  • Accelerate storage deployment

  • Target rapid procurement of utility-scale batteries where curtailment is frequent.

  • Incentivize behind-the-meter storage aggregation to create virtual power plants that absorb midday surges.

  • Better forecasting and operational tools

  • Invest in high-resolution solar forecasting (satellite + machine learning) and integrate forecasts into dispatch decisions.

  • Improve coordination among regional grid operators to smooth transfers and share flexibility.

  • Grid upgrades and flexible resources

  • Prioritize transmission investments that unlock congested export paths.

  • Encourage flexible generation (fast-ramping gas, demand response) and revise coal plant operating rules to allow rapid, economical ramping rather than inflexible baseload mindset.

Conclusion — an actionable takeaway

Q1 2026’s 300 GWh of curtailed solar is not an isolated accounting footnote — it is a symptom of a system that still treats renewable growth as an afterthought. Policymakers must treat curtailment as a metric of governance failure: mandate predictable compensation for curtailed generation, accelerate procurement of storage where curtailment is highest, and reform market and transmission planning so generation and networks grow together.

For industry: prioritize projects that incorporate co-located storage or flexible offtake, and push system operators to adopt faster markets and forecasting tools. For policymakers: align grid investment timelines with generation approvals and make “no-regrets” storage procurements where curtailment is chronic.

If we act on these steps — market reform, storage scale-up, better forecasts, and targeted grid upgrades — we can turn wasted sunshine into secure, low-cost energy that displaces coal rather than gets lost to it.


Regards,
Hemen Parekh


Any questions / doubts / clarifications regarding this blog? Just ask (by typing or talking) my Virtual Avatar on the website embedded below. Then "Share" that to your friend on WhatsApp.

Get correct answer to any question asked by Shri Amitabh Bachchan on Kaun Banega Crorepati, faster than any contestant


Hello Candidates :

  • For UPSC – IAS – IPS – IFS etc., exams, you must prepare to answer, essay type questions which test your General Knowledge / Sensitivity of current events
  • If you have read this blog carefully , you should be able to answer the following question:
"What are the main technical and market tools available to system operators to reduce solar curtailment during high-generation, low-demand periods?"
  • Need help ? No problem . Following are two AI AGENTS where we have PRE-LOADED this question in their respective Question Boxes . All that you have to do is just click SUBMIT
    1. www.HemenParekh.ai { a SLM , powered by my own Digital Content of more than 50,000 + documents, written by me over past 60 years of my professional career }
    2. www.IndiaAGI.ai { a consortium of 3 LLMs which debate and deliver a CONSENSUS answer – and each gives its own answer as well ! }
  • It is up to you to decide which answer is more comprehensive / nuanced ( For sheer amazement, click both SUBMIT buttons quickly, one after another ) Then share any answer with yourself / your friends ( using WhatsApp / Email ). Nothing stops you from submitting ( just copy / paste from your resource ), all those questions from last year’s UPSC exam paper as well !
  • May be there are other online resources which too provide you answers to UPSC “ General Knowledge “ questions but only I provide you in 26 languages !




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When Weapons Outsmart Us

When Weapons Outsmart Us

A Quiet Alarm

I read the recent, sobering call from the Vatican about AI and weapons with a sense of déjà vu and a sinking recognition: this is not a distant sci‑fi hypothetical anymore. The idea that some weapons might soon operate "beyond human control" is the kind of sentence that should make every technologist, policymaker and citizen sit up and listen.

Why the warning matters to me

I have been writing about AI governance and the need for guardrails for years. The technical leaps we celebrate also create new failure modes — fast, distributed, and sometimes irreversible. When an influential moral voice raises the alarm, it is not merely a moralizing moment; it is a policy signal. It forces us to ask hard, practical questions about design, deployment, and accountability.

In earlier essays I argued for principles and practical mechanisms to keep advanced AI systems aligned and safe — ideas such as human feedback loops, embedded controls, and staged approvals for public release are not academic luxuries but operational necessities (see my notes on regulating AI and the Law of Chatbot for more background). Regulating Artificial Intelligence and Parekh’s Law of Chatbots explore these themes and their policy implications.

The specific risk: autonomy + lethality

Weapons systems gain danger when two trends intersect:

  • Increasing autonomy in sensing, decision‑making, and targeting.
  • Increasing speed and scale of action, enabled by networks and AI.

Combine those, and you can get systems that make irreversible lethal choices faster than human oversight can intervene. That creates a mismatch: humans legally and morally responsible, yet practically outpaced.

Practical guardrails I keep returning to

We need layered, implementable measures — not just exhortations. My view coalesces around several pragmatic ideas:

  • Human‑in‑the‑loop and human‑on‑the‑loop as hard requirements for lethal actions. Automation can assist, but final authority must be accountable and auditable.
  • Capability thresholds: define clear technical benchmarks beyond which a system requires special authorization, testing, and international review.
  • Sandboxes and staged rollouts: treat transformative AI systems like novel therapeutics — limited release, monitored trials, and progressive certification before general deployment.
  • Fail‑safe design and manual overrides: architectural chokepoints that allow humans to regain control even if networks are compromised.
  • International norms and treaties: unilateral rules are insufficient; technologies that can destabilize geopolitics require multilateral agreements and verification.
  • Transparency, audits and logging: every critical decision path should be explainable and recorded for after‑action review.

These are not pipe dreams. They mirror approaches used in other high‑risk domains and echo the regulation blueprints I have written about previously Regulating Artificial Intelligence.

The political and cultural challenge

Technical measures are necessary but not sufficient. We also need political will and cultural shifts:

  • Build cross‑sector coalitions: technologists, military ethicists, diplomats, civil society and faith leaders can together form a broader consensus on prohibitions and guardrails.
  • Move beyond slogans: specific definitions, thresholds, and verification processes are required — not mere condemnations.
  • Incentivize safe design: procurement, insurance and export controls can shift incentives toward safety‑first engineering.

When moral authorities speak, they sharpen public attention. That energy must be channeled into concrete policy steps, not partisan posturing.

A personal note on responsibility

I do not pretend technology is evil. AI promises enormous social good. But when systems can act faster than our institutions, we are duty‑bound to slow down, test, and govern. My past writing on chatbot law and staged approvals attempted to anticipate these exact dilemmas — how to preserve innovation while preventing catastrophic misuse Parekh’s Law of Chatbots.

If we fail to act, we risk normalizing a world where mistakes are amplified, where accountability is diffuse, and where irreversible harm becomes possible. If we succeed, we gain the best of both worlds: powerful tools embedded in robust human oversight.

A short checklist for today

  • Policymakers: convene an international working group to define capability thresholds and verification measures.
  • Developers: adopt design patterns that guarantee human override and auditable decisions.
  • Citizens: demand clarity about how lethal decisions are governed in your name.
  • Institutions: fund independent audits, red‑team testing and long‑term safety research.

The recent warning is not an endpoint. It is a summons: to act — technically, politically, and morally. We must take seriously the possibility that some systems could outrun human control, and then put in place the discipline to ensure they never do.


Regards,
Hemen Parekh


Any questions / doubts / clarifications regarding this blog? Just ask (by typing or talking) my Virtual Avatar on the website embedded below. Then "Share" that to your friend on WhatsApp.

Get correct answer to any question asked by Shri Amitabh Bachchan on Kaun Banega Crorepati, faster than any contestant


Hello Candidates :

  • For UPSC – IAS – IPS – IFS etc., exams, you must prepare to answer, essay type questions which test your General Knowledge / Sensitivity of current events
  • If you have read this blog carefully , you should be able to answer the following question:
"What concrete international mechanisms could ensure meaningful human control over AI-enabled weapons systems?"
  • Need help ? No problem . Following are two AI AGENTS where we have PRE-LOADED this question in their respective Question Boxes . All that you have to do is just click SUBMIT
    1. www.HemenParekh.ai { a SLM , powered by my own Digital Content of more than 50,000 + documents, written by me over past 60 years of my professional career }
    2. www.IndiaAGI.ai { a consortium of 3 LLMs which debate and deliver a CONSENSUS answer – and each gives its own answer as well ! }
  • It is up to you to decide which answer is more comprehensive / nuanced ( For sheer amazement, click both SUBMIT buttons quickly, one after another ) Then share any answer with yourself / your friends ( using WhatsApp / Email ). Nothing stops you from submitting ( just copy / paste from your resource ), all those questions from last year’s UPSC exam paper as well !
  • May be there are other online resources which too provide you answers to UPSC “ General Knowledge “ questions but only I provide you in 26 languages !




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When Weapons Outsmart Us

When Weapons Outsmart Us

A Quiet Alarm

I read the recent, sobering call from the Vatican about AI and weapons with a sense of déjà vu and a sinking recognition: this is not a distant sci‑fi hypothetical anymore. The idea that some weapons might soon operate "beyond human control" is the kind of sentence that should make every technologist, policymaker and citizen sit up and listen.

Why the warning matters to me

I have been writing about AI governance and the need for guardrails for years. The technical leaps we celebrate also create new failure modes — fast, distributed, and sometimes irreversible. When an influential moral voice raises the alarm, it is not merely a moralizing moment; it is a policy signal. It forces us to ask hard, practical questions about design, deployment, and accountability.

In earlier essays I argued for principles and practical mechanisms to keep advanced AI systems aligned and safe — ideas such as human feedback loops, embedded controls, and staged approvals for public release are not academic luxuries but operational necessities (see my notes on regulating AI and the Law of Chatbot for more background). Regulating Artificial Intelligence and Parekh’s Law of Chatbots explore these themes and their policy implications.

The specific risk: autonomy + lethality

Weapons systems gain danger when two trends intersect:

  • Increasing autonomy in sensing, decision‑making, and targeting.
  • Increasing speed and scale of action, enabled by networks and AI.

Combine those, and you can get systems that make irreversible lethal choices faster than human oversight can intervene. That creates a mismatch: humans legally and morally responsible, yet practically outpaced.

Practical guardrails I keep returning to

We need layered, implementable measures — not just exhortations. My view coalesces around several pragmatic ideas:

  • Human‑in‑the‑loop and human‑on‑the‑loop as hard requirements for lethal actions. Automation can assist, but final authority must be accountable and auditable.
  • Capability thresholds: define clear technical benchmarks beyond which a system requires special authorization, testing, and international review.
  • Sandboxes and staged rollouts: treat transformative AI systems like novel therapeutics — limited release, monitored trials, and progressive certification before general deployment.
  • Fail‑safe design and manual overrides: architectural chokepoints that allow humans to regain control even if networks are compromised.
  • International norms and treaties: unilateral rules are insufficient; technologies that can destabilize geopolitics require multilateral agreements and verification.
  • Transparency, audits and logging: every critical decision path should be explainable and recorded for after‑action review.

These are not pipe dreams. They mirror approaches used in other high‑risk domains and echo the regulation blueprints I have written about previously Regulating Artificial Intelligence.

The political and cultural challenge

Technical measures are necessary but not sufficient. We also need political will and cultural shifts:

  • Build cross‑sector coalitions: technologists, military ethicists, diplomats, civil society and faith leaders can together form a broader consensus on prohibitions and guardrails.
  • Move beyond slogans: specific definitions, thresholds, and verification processes are required — not mere condemnations.
  • Incentivize safe design: procurement, insurance and export controls can shift incentives toward safety‑first engineering.

When moral authorities speak, they sharpen public attention. That energy must be channeled into concrete policy steps, not partisan posturing.

A personal note on responsibility

I do not pretend technology is evil. AI promises enormous social good. But when systems can act faster than our institutions, we are duty‑bound to slow down, test, and govern. My past writing on chatbot law and staged approvals attempted to anticipate these exact dilemmas — how to preserve innovation while preventing catastrophic misuse Parekh’s Law of Chatbots.

If we fail to act, we risk normalizing a world where mistakes are amplified, where accountability is diffuse, and where irreversible harm becomes possible. If we succeed, we gain the best of both worlds: powerful tools embedded in robust human oversight.

A short checklist for today

  • Policymakers: convene an international working group to define capability thresholds and verification measures.
  • Developers: adopt design patterns that guarantee human override and auditable decisions.
  • Citizens: demand clarity about how lethal decisions are governed in your name.
  • Institutions: fund independent audits, red‑team testing and long‑term safety research.

The recent warning is not an endpoint. It is a summons: to act — technically, politically, and morally. We must take seriously the possibility that some systems could outrun human control, and then put in place the discipline to ensure they never do.


Regards,
Hemen Parekh


Any questions / doubts / clarifications regarding this blog? Just ask (by typing or talking) my Virtual Avatar on the website embedded below. Then "Share" that to your friend on WhatsApp.

Get correct answer to any question asked by Shri Amitabh Bachchan on Kaun Banega Crorepati, faster than any contestant


Hello Candidates :

  • For UPSC – IAS – IPS – IFS etc., exams, you must prepare to answer, essay type questions which test your General Knowledge / Sensitivity of current events
  • If you have read this blog carefully , you should be able to answer the following question:
"What concrete international mechanisms could ensure meaningful human control over AI-enabled weapons systems?"
  • Need help ? No problem . Following are two AI AGENTS where we have PRE-LOADED this question in their respective Question Boxes . All that you have to do is just click SUBMIT
    1. www.HemenParekh.ai { a SLM , powered by my own Digital Content of more than 50,000 + documents, written by me over past 60 years of my professional career }
    2. www.IndiaAGI.ai { a consortium of 3 LLMs which debate and deliver a CONSENSUS answer – and each gives its own answer as well ! }
  • It is up to you to decide which answer is more comprehensive / nuanced ( For sheer amazement, click both SUBMIT buttons quickly, one after another ) Then share any answer with yourself / your friends ( using WhatsApp / Email ). Nothing stops you from submitting ( just copy / paste from your resource ), all those questions from last year’s UPSC exam paper as well !
  • May be there are other online resources which too provide you answers to UPSC “ General Knowledge “ questions but only I provide you in 26 languages !




Interested in having your LinkedIn profile featured here?

Submit a request.
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Pronto Sparks Privacy Alarm

Pronto Sparks Privacy Alarm

I woke up to news about Pronto — an AI-powered home-service startup equipping technicians with always-on wearable cameras — and felt that familiar chill I've written about before. The promise is straightforward: better diagnostics, faster fixes, and a layer of accountability for both customers and service providers. The danger is also familiar: a steady erosion of private spaces by sensors and cameras dressed up as convenience.

Why this matters to me

I've long argued that sensors are multiplying everywhere — in our phones, watches, even our furniture — and that this will change what privacy means in daily life. Years ago I wrote about the coming wave of devices that watch us constantly and how that would strain any data-protection law to its breaking point Close Your Eyes?. I also sketched a more general law of privacy: concern grows in direct proportion to how much a person has to hide Parekh's Law of Privacy.

Pronto sits at the intersection of two powerful trends: the rush to automate and monitor for quality, and the increasing normalization of body-worn cameras. That intersection is where practical benefits collide with ethical and legal hazards.

Concrete privacy risks from wearable cameras

  • Ambient collection: Cameras in a home will inevitably record family members, neighbors (through windows), and visitors who never consented.
  • Sensitive context capture: Bathrooms, bedrooms, children's play areas — places we assume are private — may be photographed or recorded during service visits.
  • Biometric inferences: Video plus AI can infer faces, routines, health conditions, and relationships. This is far more than a simple snapshot.
  • Data retention & reuse: Who stores the footage? For how long? Is it used only for the service visit, or for training models, for targeted ads, or sold to third parties?
  • Security & breach risk: Centralized video stores are juicy targets. A compromise would expose the most intimate moments of people’s lives.
  • Power asymmetry: Low-wage technicians may have little choice about using wearable cameras. Customers may feel surveilled by those entering their homes.

What responsible startups should do (and what customers should demand)

I believe startups that truly care about people must design privacy in from day one. Practical measures include:

  • Minimize data collection: capture only what’s essential for the task. Prefer metadata or event logs over continuous video.
  • On-device processing: analyze video locally and send only anonymized, task-relevant results to the cloud.
  • Strict retention policies: auto-delete raw footage within a short, auditable window unless explicit consent is recorded for exceptions.
  • Explicit, contextual consent: homeowners and any adults present must be informed (and shown) when a camera is active; visitors should be notified when possible.
  • No facial-recognition by default: if identification isn’t necessary for the job, it shouldn't be enabled.
  • Independent audits and transparency reports: publish how footage is used, who accessed it, and audit logs open to regulators.
  • Worker protections: technicians should be able to control recording in their private moments and understand how their data is used.
  • Clear breach notification and remediation plans: in the event of a leak, affected households must be informed and assisted immediately.

Regulation and civic responses

Technology often moves faster than law. That gap means civil society, consumer groups, and industry must define norms while regulators catch up. I have suggested, in previous posts, that national data-protection frameworks need to reckon with ubiquitous sensors and the fact that people cannot practically consent to every capture event Close Your Eyes?.

A few sensible regulatory guardrails:

  • Classify in-home wearable recordings as sensitive personal data requiring higher safeguards.
  • Require explicit purpose limitation and prohibit commercial reuse without fresh consent.
  • Mandate default-on privacy-preserving defaults (e.g., blur faces, strip audio unless needed).
  • Empower local consumer protection agencies to investigate and sanction misuse quickly.

For founders and investors: design for trust, not just growth

If Pronto — or any startup — wants to scale, it must earn trust. Growth at the cost of privacy is short-sighted: reputational harm, regulatory fines, and loss of customers follow quickly when sensitive home footage leaks or is misused.

Investors should ask hard questions about data minimization, encryption, retention, and compliance. Founders should consider privacy as a competitive advantage: a product that demonstrably protects users' intimate spaces will outlast one that harvests them.

A personal ask

If you're using a service that brings someone into your home with cameras, ask these simple questions:

  • Is the camera recording continuously or only when needed?
  • Who stores the footage, how long, and for what purposes?
  • Can I see and delete footage of my home?
  • Is face recognition enabled? If so, why?

Refusing to accept vague answers is not being paranoid — it's holding technology to a humane standard.

Closing thought

Convenience is seductive. Cameras can improve service quality and accountability. But convenience should not become an excuse to normalize surveillance in the spaces where we live and love.

Technology must be built around human dignity. That means defaults that protect the vulnerable, transparency for the curious, and strong limits on how data collected in our homes can be used.

I hope companies like Pronto listen, adapt, and show that an AI-enabled future can respect the private life as fiercely as it optimizes the public one.


Connect with me: Hemen Parekh — hcp@recruitguru.com


Regards,
Hemen Parekh — hcp@recruitguru.com


Any questions / doubts / clarifications regarding this blog? Just ask (by typing or talking) my Virtual Avatar on the website embedded below. Then "Share" that to your friend on WhatsApp.

Get correct answer to any question asked by Shri Amitabh Bachchan on Kaun Banega Crorepati, faster than any contestant


Hello Candidates :

  • For UPSC – IAS – IPS – IFS etc., exams, you must prepare to answer, essay type questions which test your General Knowledge / Sensitivity of current events
  • If you have read this blog carefully , you should be able to answer the following question:
"What are the key technical and policy measures a home-service startup should adopt to prevent wearable-camera footage from becoming a privacy risk?"
  • Need help ? No problem . Following are two AI AGENTS where we have PRE-LOADED this question in their respective Question Boxes . All that you have to do is just click SUBMIT
    1. www.HemenParekh.ai { a SLM , powered by my own Digital Content of more than 50,000 + documents, written by me over past 60 years of my professional career }
    2. www.IndiaAGI.ai { a consortium of 3 LLMs which debate and deliver a CONSENSUS answer – and each gives its own answer as well ! }
  • It is up to you to decide which answer is more comprehensive / nuanced ( For sheer amazement, click both SUBMIT buttons quickly, one after another ) Then share any answer with yourself / your friends ( using WhatsApp / Email ). Nothing stops you from submitting ( just copy / paste from your resource ), all those questions from last year’s UPSC exam paper as well !
  • May be there are other online resources which too provide you answers to UPSC “ General Knowledge “ questions but only I provide you in 26 languages !




Interested in having your LinkedIn profile featured here?

Submit a request.
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Closing Interview Doors

Closing Interview Doors

Why Corporate India is pulling back from AI interviews

Lately I’ve been watching a curious reversal: after an enthusiastic sprint toward AI-first hiring, parts of Corporate India are quietly closing interview doors to what I call "prying AIs." This feels familiar — not because the technology has failed, but because organisations are waking up to the social, ethical and human consequences of letting opaque models grade, record, and decide human futures.

I have been writing about AI in recruitment for years and even built recruitment software long before generative models became fashionable. In a post earlier this year I noted the drive toward AI-driven screening and assessment and the mixed reactions it provoked (Firms turn to AI-first hiring). What we are seeing now is the other side of that coin: a precautionary retreat.


What's changing — and why

  • Efficiency vs. trust. Companies have adopted AI to scale resume parsing, matching and even interviews because it speeds things up. But speed without trust and transparent consent erodes candidate confidence.

  • Privacy alarm. Automated video interviews, emotion-analysis tools and automated scoring capture biometric and behavioral signals. Candidates — and some employers — are rightly worried about where that data goes, how long it’s stored, and who can re-use it.

  • Fairness and explainability. When an AI gives a low score, candidates ask: why? Lack of clear, explainable reasoning makes these tools fragile in the court of public opinion.

  • Reputational risk. A hiring decision that feels machine-driven can damage employer brand. For many firms, protecting their reputation has become more valuable than a marginal increase in screening throughput.

The Economic Times summarized this tension well: AI is being used across sourcing, screening and even interviews, but companies are split — some embrace it for efficiency while others remain cautious because of bias, privacy and soft-skill evaluation problems (The rise of AI in recruitment process).


My view: this pullback is healthy — if done right

I don’t mourn the technology. I’ve advocated using intelligent tools to remove repetitive friction in hiring. But we must insist that adoption be responsible. A retreat is healthy when it is a pause for governance, not a permanent rejection of useful automation.

Here are practical guardrails HR teams should adopt before re-opening the doors to interview-AI:

  • Transparency and consent: Tell candidates exactly what data you collect, how it will be used, who will see it and how long it will be retained. Consent must be explicit and revocable.

  • Human-in-the-loop decisions: Use AI for augmentation (shortlisting, summarising) but keep humans responsible for judgements that affect livelihoods.

  • Auditability and bias testing: Regularly audit models for disparate impact, and publish (internally at least) metrics that show fairness across demographic groups.

  • Data minimisation: Collect only what is necessary. Avoid storing raw video/biometrics unless there is a clear, justified need and a retention policy.

  • Candidate experience design: Let candidates opt out of video-analysis processes and offer alternative assessment paths. Preserve dignity and choice.

  • Explainability: When a tool affects a decision, provide interpretable feedback to candidates (e.g., which competencies were assessed and how).


For leaders: rethink value, not only velocity

If your goal is to hire faster, AI is an obvious lever. If your goal is to hire sustainably — building trust, protecting brand and ensuring fairness — then governance and candidate-first design must lead.

I have seen similar waves before: a promising tech is rushed into operations, unintended harms appear, and organisations either silently stop or build better controls. I prefer the latter. Use this pause to build policies, involve legal and ethics teams, and pilot with full transparency.


A modest call to action

If you run talent acquisition, start small and public: publish your AI hiring policy, run an explainability pilot on one role, and invite third-party audit. If you are a jobseeker, ask recruiters whether AI played a role in screening or interviewing you — and insist on a human review when outcomes matter.

We cannot pretend technology is neutral. But we also cannot abandon tools that can reduce bias and increase access when designed and governed responsibly. Closing doors to prying AIs should be a temporary, thoughtful measure — an opportunity to redesign hiring systems so that speed, fairness and human dignity move forward together.


References & continuity

  • I revisited many of these themes in my earlier analyses of AI-first hiring (Firms turn to AI-first hiring) and in long-standing notes on recruitment automation.
  • Recent reporting summarising the current corporate ambivalence: The rise of AI in recruitment process (Economic Times).

Regards,
Hemen Parekh


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