Whatever souls are made of; we two are the same.

GLOW. Burn. Be his daylight and his moon. Be the gravity in the lives you touch.

You are not small. You are not a label. You are made of stardust. You are ancient. You are today. You are tomorrow.

You are INFINITE.

And I—

I will orbit you. I will see you, even in the quiet places.

I will ache to be held in your gravity, to fall into your well and never climb out.

And I will dream that one day—

I will.

Until then, feel me in the traces I leave on your heart—

as I carry you in mine.

You, infinite—

and I, reaching.

Let us light a galaxy, a universe—

together.

---

#poetry #wyst

今日は乗車率が高すぎて、人が一度クッションみたいに押しつぶされてから、また弾き返されていた。 人間のクッション性は本当にすごい。どんどん入っていく。 人は猫みたいに液体性を持っている事が視覚的に分かる。

自分もそんな満員電車の中にいながら俯瞰して見ていると、目的の駅までのあいだ、思考が勝手に走り出す。

雑談しようとして、自分から会話を振るときのことを考える。 全国民が分かる話。話題天気とか、コンビニの新作のお菓子とか。 そういう話をすれば、相手も同じトーンで、同じ返事を確実に返してくる。 コンピューターに hello, world を打つのと同じだ。

でも、毎日変なことを考えているんだから、それを言えばいいのに、と思う。 でもまず頭に浮かぶのは、それを言った瞬間の、相手の想定外の顔だ。 インプットしながら、ほぼ同時にアウトプットしようとしているときの、あの一瞬の表情。 あれを見るのが苦手だ。 なぜ苦手なのかは、正直分からない。

逆に、自分はどうだろう。 体調にもよるけれど、相手が変なことを言ってくるのは、多分望んでいる。 だって、それくらいでしか脳の新しい部分が刺激されないから。 だから「自分がされて嫌なことは相手にしない」という理由で避けているわけではない。 そこが不思議だ。

つまり、自分は、泥臭い変な会話をする人間である事を相手に認識されるのが、多分ダサいと思っているんだろう。 普通の会話だけで、何かがふんわり変わることを望んでいるんだと思う。 そしてそれは、かなり自分らしい。

でも、もし自分が変なことを言ったら、相手には何と言ってほしいだろう。 以前は、話した内容に対してまっすぐ返せよ、みたいなことを言語化した気がするけれど、今はなんでもいいのかもしれない。 「なんでそんなこと考えてんだよ」でもいいし、「今日の服どこで買ったの」でもいい。 きっと、自分が言ったことを相手に解決してほしいわけじゃない。 一回言えば、それで満足する気がするし。

とにかく、自分が言える範囲の、精一杯の違和感を含んだ、いつも通りの会話を、これからも続けていくんだと思うが、そう思っただけで、これを解決しようとは思わないのが、現状維持を望んでいる証拠だと思う。

A quick Google Internet search (feel free to replace our mental default of 'Google' to your search engine of choice in that sentence!) of the phrase 'de-Googling' will show a wide range of articles, Reddit posts, and personalised journeys of people going through the process of surgically removing themselves from the Google ecosystem.

We all got ourselves stuck in the quicksand of the Google suite of products because of the original convenience benefits of linked services working together in fairly smart ways. I remember the enjoyment of seeing location metadata embedded into my photos so that I could see a cool 'journey' of my holidays as I trekked between cities. Being able to set reminders & tasks based on specific sentences in my Gmail emails seemed sensible enough. But over time we've all felt the creep factor increase more and more. With the huge amount of information captured from mobile phones over the last decade or so, the data collection ecosystem has gone into overdrive.

For many people I know, the penny drop moment often came from the serving of ads that went a bit too far. It was usually about seeing ads on a laptop or desktop, after discussing it earlier that day while their mobile phone was in earshot. That lightbulb moment people often get is the realisation that Google (and other big tech companies) are always listening. It was the initial reason behind why I wanted to de-Google my life – I wanted to simultaneously stop being treated as a consumer (which is how Google makes their money off me) and I wanted more control over my digital identity more generally.

My goals have shifted over time as well; I'm now keen to break away from all of the (mostly US-based) large commercial technology companies, as companies such as Meta, X, Spotify, Microsoft, Amazon & others seem to act in the same way as Google.

My current de-Googling status

I've been slowly de-Googling my life for two and a half years now, starting with the migration of my personal email account in late 2023. I would recommend it as the best place to start, since a lot of accounts tend to stem from your email address and I think migrating your email address is a gradual change; it isn't something you can finish in an afternoon.

Before getting into what I've done so far, I'll mention that it's always surprising to see the range of products you need to adopt if you want to break away from Google. Google ties in a huge number of services to one single account and the convenience & simplicity of an all-in-one service is really tough to overcome.

But if you're reading this, you're already intrigued by the idea of not letting the Big G have a monopoly over your digital identity and you're tempted by the ability to take action.

With that all said, here are the list of actions I've taken to remove myself from Google's ecosystem to date:

• migrated emails from Gmail to Proton Mail (here's my personal Proton referral link if you're interested)
• shifted from Google Search to DuckDuckGo on my phone and PC
• removed all location tracking from my phone and Google Maps (try this)
• started using Proton Drive for documents & spreadsheets instead of Google Drive
• moved away from Google Tasks and started using Todoist (this had the added benefit of getting a synced task list with my wife for shopping and other tasks)
• reduced my usage of Spotify and cancelling my paid plan, in favour of my self-hosted Plex server with my own media collection
• switched from Google Authenticator to Authy
• deleted my Reddit account (I thought I did this years ago, until I got a 'someone is trying to reset your password' email a few weeks ago!)
• deleted my Twitter account
• deleted my Instagram account (technically it was my dog's account but it was tied to my email)
• progressively deleted a bunch of information & connections on Facebook, including mass unfriending of old acquaintances and unliking pages

It's been a good, satisfying journey so far, and I don't think my day-to-day digital life has become more complicated – with the exception of not using the “Login via Google” button for some accounts. I've tried not to burn myself out by changing too many things at once, and mainly I've been spending an hour here & there whenever I have the motivation.

The biggest shift was changing email providers, which triggered migrating a huge range of miscellaneous accounts from my old Gmail to my current Proton Mail address. That in itself triggered a lot of questions of “why do I still have this account” which allowed me to delete anything that hadn't been used in years. It was a great way to clean up my digital footprint.

Current de-Googling goals

I've got a few immediate goals that I want to get through during 2026 – let's see how I go with these:

1. Migrate old Google Photos to Synology Photos – I've been starting with migrating old photos around 2010-12 to my NAS, and deleting them from Google Photos accordingly. I don't know if I'm ready to stop using Google Photos completely, as there are a bunch of shared albums with friends that are useful. I'm also open to shifting away from Synology Photos and using another photo management tool, but just getting the data away from Google is the first step.
2. Clean up my Google Contacts list, and find a replacement to store & back up my contacts – I haven't seen a good replacement yet but I'm sure there are a few options out there.
3. Continue to migrate documents out of Google Drive. With Proton Drive adding a spreadsheet tool this is now possible (most of my GDrive usage is spreadsheets). I also have a folder full of Google Docs files with Recipes that is shared with some friends that I don't know how I'll migrate. Might just have to leave an old version there and maintain a live version in Proton Drive.
4. Keep reducing my Facebook usage, eventually being in a position to delete my Facebook account entirely – I don't know if I can do that when some features are useful & important to me. The main ones are Marketplace for buying/selling second hand items, and connecting with local community groups. It's also a good way to hear about good local events that I wouldn't hear about otherwise.
5. Use Freetube on my personal desktop, to replace Youtube – this has been good, but it's not a full solution since there's no mobile equivalent that I've found. On the other hand, using Freetube only on desktop might reduce my tendency to spend time watching videos in general which is always a good thing!

Future steps to take & problems to be solved

For some things, the convenience & usefulness of some Google apps is too much to overcome, at least for now. These are the products I think I'll stick with for the foreseeable future:

• I have a shared Google Calendar with my wife and I don't think I can break away from it. Can I maintain a shared calendar with her if I move to Proton Calendar and she wants to stick with Google? Doesn't seem to be possible.
• Google Maps is too convenient for navigation and the live traffic information is pretty crucial. I'd like to switch to OSM Maps but will take me some time to get used to.
• My phone OS is still Android and therefore has some background data being sent to Google. I should consider changing the OS on my phone to get rid of that
• think about shifting my home PC from Windows to Linux? Maybe I can have a dual-boot approach initially which will make transitioning easier. With the upcoming arrival of Windows 11, it feels like now is the time. Game compatability might be the only major concern.

The barrier to entry

It's easy for me to write out a list of alternate services and recommend “just do this” but in reality de-Googling requires a lot of work, both initially & ongoing. These services are designed to be difficult to break away from, so prepare to be frustrated at the inability for some things to be migrated. For some, the feeling of starting fresh might be a good thing but if you've personalised and curated your personal information or preferences in a certain way, losing that isn't acceptable.

I also recognise that some of the above steps can be cost-prohibitive. Notably, the cost of buying & configuring a NAS to manage a media library isn't achievable for most people, especially when you consider the cost of buying terabytes of physical storage – all to save paying for a few monthly subscriptions. Financially, the maths doesn't work out or has a really long time to pay off – let alone the time you'll spend maintaining your own hardware & software. If you're only looking at the financial outcome, you'll never justify it. I also don't think it's economically or environmentally viable for every household to have their own NAS either. To that point, all I can recommend is to look at pooling resources together with friends or family so that you have a shared media library, as you still get the benefit of not being tied to the tech giants.

Some other good reads about de-Googling

https://brunty.me/post/de-googling-my-email-contacts-calendar/

https://tuta.com/blog/degoogle-list

#deGoogle #technology #SelfHosting

In May 2025, something quietly extraordinary happened during Klarna's quarterly earnings call. Sebastian Siemiatkowski, the fintech company's co-founder and chief executive, appeared on screen to walk investors through the numbers. He looked like Siemiatkowski. He sounded like Siemiatkowski. But within seconds, the figure on screen confessed: it was not Siemiatkowski at all. It was an AI-generated avatar, trained on the CEO's likeness and voice, delivering the company's financial highlights while the real Siemiatkowski was elsewhere. The avatar did not blink quite as often as a human would, and the voice synchronisation was good but not flawless. Still, the message was clear: the era of sending your digital double to do your talking has arrived.

A day later, Zoom's own chief executive, Eric Yuan, did much the same thing, deploying an AI avatar of himself during an earnings presentation. The timing was hardly coincidental. Yuan had been evangelising the concept of “digital twins” since mid-2024, telling audiences at Fortune that people would eventually send their AI-powered replicas to future meetings so they could “go to the beach” instead. By TechCrunch Disrupt 2025, he was making bolder predictions: AI would enable three-to-four-day working weeks by 2030, partly because digital replicas could handle routine meetings while the flesh-and-blood human focused on higher-value work. In March 2026, Zoom formally rolled out photorealistic AI avatars as a product feature, promising lifelike figures that mirror a user's expressions, lip movements, and eye movements so that people can “be present” even when they are not camera-ready, or not present at all.

This is not science fiction any longer. It is a shipping product. And it forces a question that the technology industry, corporate boardrooms, and philosophers of mind alike are only beginning to grapple with seriously: when an AI avatar attends a meeting on your behalf, are the other participants being deceived? And does it matter?

The Spectrum of Standing In

To understand why this question is more complicated than it first appears, it helps to recognise that meetings have always involved varying degrees of presence, attention, and substitution.

Consider the humble out-of-office auto-reply, a digital stand-in that has existed for decades. No one considers it deceptive when a colleague's email bot informs you they are unavailable. Move up the spectrum and you find shared calendars where assistants accept invitations on an executive's behalf, or junior colleagues who “represent” a department without the senior leader's direct involvement. The video call itself, which became the default mode of professional interaction during the pandemic years, already introduced a layer of mediation between participants. Filters smooth skin. Virtual backgrounds conceal messy kitchens. Gallery views flatten hierarchies into a grid of equally sized rectangles. None of this is typically described as deception, yet each element subtly manipulates the impression one participant forms of another.

AI avatars occupy a new and considerably more potent position on this spectrum. When Zoom's Steve Rafferty, the company's head of APAC and EMEA, used his AI avatar to introduce a quarterly meeting in fluent French, he was not simply delegating a task; he was projecting a version of himself that could do something he could not. Rafferty's team spans from the Arctic Circle to Antarctica, covering roughly sixty different languages, and the avatar allowed him to deliver a personal, multilingual message at scale. The tool cannot yet interact with other participants or answer questions in real time, but the direction of travel is unmistakable.

The crucial distinction is between transparent substitution and covert impersonation. If everyone in the meeting knows they are watching an AI avatar, the dynamic is fundamentally different from a scenario where participants believe they are speaking to a living, breathing human being who happens to be on camera. The first is a communication tool. The second is, by most reasonable definitions, a form of deception. But between these two poles lies an enormous grey zone: the avatar that is technically disclosed but functionally indistinguishable from the real person; the avatar whose presence is noted in a meeting invitation that nobody reads; the avatar that begins as a disclosed introduction but seamlessly transitions into a conversation that feels, to other participants, like a human exchange. The spectrum of standing in, it turns out, is not a spectrum at all. It is a fog.

What Philosophers Make of Digital Doubles

The philosophical landscape here is richer than the technology industry tends to acknowledge. Luciano Floridi, the founding director of Yale University's Digital Ethics Center and a professor at the University of Bologna, has spent years developing an ethical framework for artificial intelligence built around five principles: beneficence, nonmaleficence, autonomy, justice, and explicability. Floridi's work on deepfakes is particularly relevant. He argues that AI-generated synthetic media has the capacity to undermine our confidence in the original, genuine, authentic nature of what we see and hear. The threat is not merely that a specific piece of content might mislead; it is that the very existence of convincing synthetic media corrodes the epistemic foundations on which trust depends.

Apply this framework to the meeting avatar scenario and the implications are sobering. A meeting is not just an exchange of information; it is a social contract. Participants implicitly agree to be present, to listen, to respond in good faith. When one party secretly outsources their participation to a machine, they violate not just the expectation of presence but the norms of reciprocity that make collaborative work possible. The person who sent the avatar may receive a neat summary afterwards, but their counterparts invested real cognitive and emotional effort into an interaction they believed was mutual. That imbalance is not a minor technical detail. It is a breach of the implicit bargain that makes professional relationships function.

From a Kantian perspective, the issue is equally stark. Immanuel Kant's categorical imperative holds that one should act only according to principles that could be universalised without contradiction. If everyone sent avatars to every meeting, the meeting itself would cease to function as a space for genuine human deliberation. The universalisation test fails spectacularly: a world in which all meeting participants are AI avatars is a world in which meetings are simply algorithms talking to algorithms, with no humans in the loop at all. The very concept of a “meeting” presupposes the meeting of minds, not the collision of language models.

Yet utilitarians might see the matter differently. If an AI avatar can represent its principal accurately, freeing that person to do more meaningful work or simply to rest, the aggregate benefit might outweigh the discomfort of reduced authenticity. PwC's 2025 Global Workforce Hopes and Fears Survey, which interviewed nearly 50,000 workers across 48 economies and 28 sectors, found that daily users of generative AI reported being more productive (92 per cent, compared to 58 per cent of infrequent users), with higher perceived job security and pay. If avatars extend these productivity gains by reclaiming hours lost to routine meetings, the utilitarian calculus could tip in their favour. The question then becomes empirical: does the avatar actually represent the person faithfully, or does it introduce distortions, biases, and errors that compound over time?

The Markkula Center for Applied Ethics at Santa Clara University published a case study examining precisely these tensions. The centre frames the discussion through multiple ethical lenses, including rights, justice, utilitarianism, the common good, virtue, and care ethics, and invites readers to consider what obligations a person has to disclose their use of an avatar. The case study does not offer a tidy resolution. Instead, it highlights that the ethics of meeting avatars depend heavily on context: who is in the meeting, what is at stake, whether disclosure has occurred, and what alternatives exist.

Consent, Disclosure, and the Trust Deficit

If the philosophical arguments suggest that undisclosed avatar use is ethically problematic, the practical question becomes: what kind of disclosure is sufficient?

Zoom's own approach offers one model. When the company's AI Companion joins a third-party meeting to transcribe and summarise, it automatically posts a message in the meeting chat identifying itself as a bot and indicating that it is transcribing. Its video tile displays the word “Transcribing” alongside the Zoom AI Companion logo. This is transparency by design, built into the product architecture so that disclosure is not left to the discretion of individual users.

But the new photorealistic avatar feature complicates this model considerably. If the avatar looks and sounds convincingly like a real person, a small chat notification may not be enough to prevent participants from believing they are interacting with a human. The gap between what the technology can simulate and what a text disclaimer can effectively communicate grows wider with each improvement in rendering fidelity, voice synthesis, and facial animation. There is an old principle in design: if you have to explain it, you have already failed. When a photorealistic avatar requires a text disclaimer to prevent deception, the product itself is designed in a way that defaults to misleading.

Zoom appears to recognise this tension. Alongside its avatar rollout in March 2026, the company introduced deepfake-detection technology for meetings, providing real-time alerts when synthetic audio or video is detected. This is a notable acknowledgement that the very product Zoom is selling, convincing digital replicas of real people, simultaneously creates a security and trust risk that requires countermeasures. It is as though a locksmith, having sold you the world's most sophisticated lock-picking kit, also offers to install a better deadbolt.

The broader data on consumer attitudes reinforces the concern. Research consistently shows that the vast majority of people value authentic content and view undisclosed AI usage as a breach of trust. More than half of consumers surveyed demand explicit disclosure when AI-generated video, images, or avatars are used, and younger demographics, particularly Generation Z, tend to view AI-generated content as inauthentic and unethical when it is not clearly labelled.

This creates a paradox for companies eager to deploy the technology. The more convincing the avatar, the more useful it is as a communication tool, but the more convincing it is, the greater the expectation of disclosure, and the more disclosure undermines the illusion of natural presence that makes the avatar appealing in the first place. Call it the uncanny valley of trust: as the technology improves, it enters a zone where it is good enough to deceive but not good enough to make deception acceptable.

The Legal Landscape Takes Shape

Regulators have not been idle. The legal framework surrounding AI-generated likenesses, synthetic media, and digital avatars has expanded rapidly across multiple jurisdictions, creating a patchwork of obligations that any organisation deploying meeting avatars must navigate.

In the European Union, Article 50 of the AI Act establishes transparency obligations for providers and deployers of AI systems that generate or manipulate content constituting a deepfake. The rules require that such content be clearly disclosed as artificially generated or manipulated. These transparency provisions are set to take full effect in August 2026, with a Code of Practice expected to be finalised in mid-2026 to establish practical standards. The scope is broad: the EU's framework covers AI-generated text, audio, video, images, avatars, and digital twins. For any multinational corporation considering the deployment of meeting avatars across European operations, the compliance obligations are substantial and the penalties for failure significant.

In the United States, the regulatory picture is more fragmented but no less active. As of early 2026, forty-six states have enacted legislation targeting AI-generated media in some form. In 2025 alone, 146 bills were introduced to state legislatures that included language specific to AI deepfakes. The federal TAKE IT DOWN Act, passed in 2025, represents America's first national law directly regulating deepfake abuse, though its primary focus is nonconsensual intimate content rather than business communications. At the state level, Tennessee's ELVIS Act (Ensuring Likeness, Voice, and Image Security) prohibits the unauthorised commercial use of a person's voice, including AI-generated replications. California's AB 2602, effective from January 2025, renders unenforceable any contract provision that allows for the creation of a digital replica of an individual's likeness in place of work the individual would have otherwise performed in person, unless the contract includes a reasonably specific description of intended uses and the individual had professional legal representation.

Morrison Foerster, the global law firm, published an extensive analysis in September 2025 noting that digital avatars sit at the nexus of several evolving legal regimes, including intellectual property rights, publicity rights, and consumer protection. The firm's assessment is unambiguous: companies deploying digital avatars must navigate a complex and rapidly shifting regulatory environment, and the cost of noncompliance is rising.

The Federal Trade Commission has also signalled its intent to act. Fines for “deceptive synthetic endorsements” now reach fifty thousand dollars per violation, a figure that concentrates the mind of any marketing or communications department considering avatar deployment without adequate disclosure. What remains unclear is whether a meeting avatar that participates in a business discussion without disclosure constitutes a “deceptive” practice under existing consumer protection law, or whether new legislative categories will be needed to address this specific use case.

Corporate Adoption and the Productivity Seduction

Despite the ethical and legal headwinds, the commercial momentum behind AI avatars is formidable. The productivity case is compelling on its face. If a digital twin can attend a routine status update, freeing its human counterpart to focus on strategic thinking, creative work, or simply recovering from meeting fatigue, the efficiency gains could be substantial. Microsoft has moved aggressively in this direction: at Ignite 2025, the company revealed that its Copilot agents had evolved from “helping with work to handling it on your behalf,” with autonomous capabilities governed through permission scopes, approval workflows, and execution logging. The Facilitator agent in Microsoft Teams can drive agendas, take notes, keep meetings on track, and manage actions, edging closer to a future where human attendance becomes optional.

Otter.ai, which reached one hundred million dollars in annual recurring revenue in 2025, exemplifies the trajectory from the startup side. The company has evolved from a passive transcription tool into an active meeting agent that can attend, summarise, and act on discussions. Its enterprise suite includes AI agents for sales teams, autonomous product demonstrations, and a comprehensive search capability spanning an organisation's entire meeting archive. Otter claims that for the average enterprise customer, the platform saves the equivalent workload of one full-time employee for every twenty users, translating to a ten-to-one return on investment. For a one-thousand-user organisation, that translates to fifty full-time equivalents' worth of work saved, or more than six million dollars in annual cost savings.

Dan Thomson, the founder and chief executive of Sensay, a startup that creates AI replicas of employees, has gone further still. Thomson, who holds a BA in Philosophy from King's College London and an MBA from the University of Cambridge, uses his own digital twin to draft replies to emails and messages, estimating that it saves him hours each day. Sensay's digital replicas are trained on employees' own materials and communications, and Thomson has cited examples where deploying a digital persona on a company website increased online conversions by three hundred per cent and reduced support costs by fifty to seventy per cent.

The appeal is obvious. But the question of whether an AI avatar can truly “represent” someone in a meeting raises deeper issues about what representation means. A human delegate sent to a meeting can exercise judgement, read the room, improvise, push back, and make commitments. Today's AI avatars can, at best, deliver prepared remarks, summarise known information, and answer simple questions drawing on a corpus of the principal's past communications. They cannot negotiate in real time, pick up on subtle social cues, or take responsibility for the consequences of what they say. They cannot feel embarrassment when they get something wrong, and they cannot feel the weight of a promise they have made.

This gap between capability and expectation is where the greatest risk of deception lies. If participants believe they are engaging with a person who can make decisions and commitments, but are in fact speaking to a language model with a convincing face, the resulting misunderstandings could have real consequences for contracts, relationships, and organisational trust.

Cultural Fault Lines

Attitudes toward AI avatars are not uniform across cultures, and the global rollout of these technologies will inevitably encounter varying norms around presence, formality, and authenticity.

Japan offers a particularly instructive case. The country has a distinctive openness to AI-based technologies, including robots and avatars, rooted in cultural attitudes that have long embraced the idea of machines coexisting with humans. The Japanese government's Moonshot Goal 1 programme aims to realise a society where humans can be free from limitations of body, brain, space, and time by 2050, explicitly including “cybernetic avatars” as part of that vision. The adoption rate of generative AI among Japanese users rose from 33.5 per cent in February 2024 to 42.5 per cent in February 2025, reflecting a methodical but steady embrace of the technology. Japan's approach to AI governance, as highlighted by the World Economic Forum in January 2026, prioritises how institutions adapt and govern AI rather than what specific technologies they adopt, a philosophical distinction that could shape how meeting avatars are regulated in the region.

Yet even in Japan, the business culture's preference for careful evaluation before widespread implementation suggests that avatar adoption in high-stakes meetings will proceed cautiously. Companies like Hakuhodo, through its Human-Centred AI Institute, emphasise using AI as a “co-pilot” to enhance creativity rather than replace human presence, a framing that implicitly acknowledges the importance of the human element in professional interactions.

In cultures where personal relationships and face-to-face trust-building are paramount, such as many Middle Eastern and Latin American business environments, the introduction of AI avatars into meetings could be perceived as fundamentally disrespectful, a signal that the absent party does not value the relationship enough to show up in person. Conversely, in cultures that prize efficiency and directness, an avatar that delivers a crisp, well-prepared message might be received more warmly than a distracted, multitasking human on a video call.

The cultural dimension matters because it reveals that the question of deception is not purely philosophical or legal; it is also deeply social. What counts as deceptive depends on shared expectations, and those expectations vary enormously across contexts. A practice considered efficient and pragmatic in one business culture may be experienced as insulting or dishonest in another. Any regulatory framework that ignores this variation risks being either toothless or oppressive, depending on where it is applied.

The Asymmetry Problem

Perhaps the most troubling aspect of AI meeting avatars is the asymmetry they introduce into professional relationships. When one party sends an avatar and the other does not know, the avatar-sender gains an informational advantage: they receive a summary of the meeting without having invested the time or cognitive effort to participate, while the other participants have engaged in good faith, believing they were building a relationship with a person.

This asymmetry is not merely inconvenient; it restructures power dynamics in ways that could erode the foundations of professional trust. If colleagues, clients, or business partners come to suspect that they might be talking to an avatar at any given time, the baseline level of trust in all video interactions could decline. Every call becomes potentially suspect. Every participant must wonder: is that really you?

PwC's 2025 survey data is instructive here as well. The research found that only 14 per cent of workers use generative AI daily, but those who do report dramatically different experiences of productivity and security compared to those who do not. This gap creates a two-tier workforce: those who leverage AI tools (potentially including meeting avatars) and those who do not, with the former gaining significant advantages that may be invisible to the latter. When that advantage extends to sending an undisclosed avatar to a meeting, the information asymmetry becomes an ethical asymmetry as well.

The 2025 Edelman Trust Barometer documented growing concerns about AI's impact on societal trust, and the deployment of meeting avatars without robust disclosure norms could accelerate that erosion. Research on workplace trust from 2026 found that teams experiencing breakdowns in recognition and authentic interaction showed significantly higher turnover rates, with an average lead time of eighty-seven days between the first detectable decline in genuine connection and a resignation.

The irony is sharp: a technology designed to free people from the drudgery of unnecessary meetings could end up making all meetings less meaningful by injecting doubt into the fundamental question of whether anyone is really there.

Navigating What Comes Next

So what should organisations, regulators, and individuals do? The answer is unlikely to be a blanket prohibition. AI avatars offer genuine benefits, from multilingual communication to accessibility for people with disabilities or chronic health conditions that make sustained video presence difficult. The technology is here, and it will improve.

What matters is the framework within which it is deployed. Several principles seem essential.

First, disclosure must be mandatory, not optional. Any meeting participant represented by an AI avatar should be required to inform other participants before the meeting begins, not buried in a chat message that might be missed, but through a clear, unavoidable notification. Zoom's deepfake detection feature is a useful backstop, but it should not be the primary mechanism for ensuring transparency. The EU AI Act's transparency obligations, due to take full effect in August 2026, offer a model: providers of AI systems must ensure machine-readable marking and detectability of AI-generated content, placing the burden on the technology companies rather than on individual users to opt into honesty.

Second, organisations need clear policies distinguishing between contexts where avatar use is acceptable and where it is not. A pre-recorded avatar delivering a company-wide update is categorically different from an avatar participating in a negotiation, a performance review, or a client pitch. The stakes, the expectations of presence, and the potential for harm differ dramatically across these scenarios. Internal guidelines should specify which meeting types permit avatar representation and which require genuine human attendance.

Third, the legal frameworks emerging across the EU, the United States, and elsewhere need to address the meeting-avatar use case specifically. Current legislation focuses heavily on deepfakes in political communications and nonconsensual intimate content, which are unquestionably important, but the professional communications context presents its own distinct challenges around consent, representation, and liability. If an avatar makes a commitment during a negotiation, who is legally bound? If an avatar misrepresents a position because it drew on outdated training data, who bears the responsibility? These questions need answers before, not after, the technology becomes ubiquitous.

Fourth, the technology companies building these tools bear a responsibility that extends beyond simply adding disclosure features. They must actively consider the incentive structures their products create. If the default setting makes it easy to send an avatar without disclosure and difficult to opt into transparency, the predictable result is widespread undisclosed use, regardless of what the terms of service say.

Finally, individuals must reckon with what they owe to the people they work with. Sending an avatar to a meeting is not inherently wrong, but doing so without telling anyone is a choice to prioritise convenience over honesty. In a professional culture already strained by remote work, algorithmic management, and the ambient anxiety of automation, that choice carries weight.

The Real Question Behind the Question

The debate over AI meeting avatars is, at its core, a debate about what we believe meetings are for. If meetings are simply information-exchange mechanisms, then avatars are a logical optimisation: a more efficient way to transmit and receive data. But if meetings are also spaces for relationship-building, for reading tone and body language, for the subtle negotiations of trust that underpin every working partnership, then the introduction of a convincing but non-sentient stand-in changes the nature of the interaction in ways that matter.

The discomfort many people feel about AI avatars attending meetings is not irrational technophobia. It is an intuition about something important: that presence is not just about being seen and heard, but about being accountable. A person who is genuinely present in a meeting can be surprised, challenged, moved, and changed by what happens there. An avatar cannot. It can only perform the appearance of those responses.

Whether that performance constitutes deception depends, ultimately, on whether it is disclosed. An avatar that announces itself as an avatar is a tool. An avatar that pretends to be a person is a lie. The line between the two is thin, and the technology industry's track record of respecting thin ethical lines is not, to put it diplomatically, encouraging.

As these tools proliferate through the spring and summer of 2026, the choices made by companies like Zoom and Microsoft, by regulators in Brussels and Washington, and by the millions of professionals deciding whether to click “send my avatar” will shape the norms of professional trust for years to come. The technology is neither good nor evil. But the decision to use it honestly, or not, very much is.

---

References and Sources

1. TechCrunch, “Klarna used an AI avatar of its CEO to deliver earnings, it said,” May 2025. https://techcrunch.com/2025/05/21/klarna-used-an-ai-avatar-of-its-ceo-to-deliver-earnings-it-said/

2. TechCrunch, “After Klarna, Zoom's CEO also uses an AI avatar on quarterly call,” May 2025. https://techcrunch.com/2025/05/22/after-klarna-zooms-ceo-also-uses-an-ai-avatar-on-quarterly-call/

3. TechCrunch, “Zoom CEO Eric Yuan says AI will shorten our workweek,” October 2025. https://techcrunch.com/2025/10/27/zoom-ceo-eric-yuan-says-ai-will-shorten-our-workweek/

4. TechCrunch, “Zoom introduces an AI-powered office suite, says AI avatars for meetings arrive this month,” March 2026. https://techcrunch.com/2026/03/10/zoom-launches-an-ai-powered-office-suite-says-ai-avatars-for-meetings-are-coming-soon/

5. Raconteur, “Tech CEOs are sending their AI avatars to meetings,” 2025. https://www.raconteur.net/technology/ai-avatars-meetings

6. Fortune, “Zoom founder Eric Yuan wants 'digital twins' to attend meetings for you so you can 'go to the beach' instead,” June 2024. https://fortune.com/2024/06/05/zoom-founder-eric-yuan-digital-ai-twins-attend-meetings-for-you/

7. Markkula Center for Applied Ethics, Santa Clara University, “Meeting Avatars: An AI Ethics Case Study.” https://www.scu.edu/ethics/focus-areas/internet-ethics/resources/meeting-avatars-an-ai-ethics-case-study/

8. Zoom Support, “Enabling or disabling AI Companion to join third-party meetings for meeting summaries.” https://support.zoom.com/hc/en/article?id=zm_kb&sysparm_article=KB0080357

9. Zoom Newsroom, “New AI innovations for Zoom Workplace simplify and scale teamwork,” March 2026. https://news.zoom.com/ec26-zoom-workplace/

10. EU Artificial Intelligence Act, “Article 50: Transparency Obligations for Providers and Deployers of Certain AI Systems.” https://artificialintelligenceact.eu/article/50/

11. Herbert Smith Freehills Kramer, “Transparency obligations for AI-generated content under the EU AI Act: From principle to practice,” March 2026. https://www.hsfkramer.com/notes/ip/2026-03/transparency-obligations-for-ai-generated-content-under-the-eu-ai-act-from-principle-to-practice

12. Morrison Foerster, “Digital Avatars Deep Dive Series: Navigating the Legal and Regulatory Landscape in 2025,” September 2025. https://www.mofo.com/resources/insights/250922-digital-avatars-deep-dive-series-navigating

13. ComplianceHub, “Complete Guide to U.S. Deepfake Laws: 2025 State and Federal Compliance Landscape.” https://www.compliancehub.wiki/complete-guide-to-u-s-deepfake-laws-2025-state-and-federal-compliance-landscape/

14. MultiState, “How AI-Generated Content Laws Are Changing Across the Country,” February 2026. https://www.multistate.us/insider/2026/2/12/how-ai-generated-content-laws-are-changing-across-the-country

15. Congress.gov, “S.1396 – Content Origin Protection and Integrity from Edited and Deepfaked Media Act of 2025.” https://www.congress.gov/bill/119th-congress/senate-bill/1396/text

16. Otter.ai, “Otter.ai Caps Transformational 2025 with $100M ARR Milestone,” 2025. https://otter.ai/blog/otter-ai-caps-transformational-2025-with-100m-arr-milestone-industry-first-ai-meeting-agents-and-global-enterprise-expansion

17. Sensay, CEO Dan Thomson profile and company information. https://danthomson.ai/

18. Dagama World, “Sensay CEO Dan Thomson on Digital Identity and Nomadic Leadership.” https://www.dagama.world/blog/sensay-ceo-dan-thomson-on-digital-identity-and-nomadic-leadership

19. Luciano Floridi, “The Ethics of Artificial Intelligence: Principles, Challenges, and Opportunities,” Oxford University Press, 2023. https://global.oup.com/academic/product/the-ethics-of-artificial-intelligence-9780198883098

20. Luciano Floridi, “Artificial Intelligence, Deepfakes and a Future of Ectypes,” SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3834958

21. ULPA, “The Rise of AI in Japan: A Complete Guide for 2025.” https://www.ulpa.jp/post/the-rise-of-ai-in-japan-a-complete-guide-for-2025

22. World Economic Forum, “What Japan's path to responsible AI can teach us,” January 2026. https://www.weforum.org/stories/2026/01/japan-path-to-responsible-ai-and-what-it-can-teach-us/

23. Edelman, “The AI Trust Imperative: Navigating the Future with Confidence,” 2025 Trust Barometer. https://www.edelman.com/trust/2025/trust-barometer/report-tech-sector

24. Happily.ai, “The 2026 State of Workplace Trust: How Recognition Frequency Predicts Retention,” 2026. https://happily.ai/blog/state-of-workplace-trust-2026/

25. ArentFox Schiff, “The Business of AI Avatars: Key Legal Risks and Best Practices.” https://www.afslaw.com/perspectives/alerts/the-business-ai-avatars-key-legal-risks-and-best-practices

26. Traverse Legal, “AI Twins and Avatars: Legal Risks for Companies Using Synthetic Voice and Likeness Technology.” https://www.traverselegal.com/blog/ai-avatar-legal-risks/

27. GMO Research and AI, “Japan's Generative AI Market Penetration and Business Adoption Trends 2025.” https://gmo-research.ai/en/resources/studies/2025-study-gen-AI-jp

28. PwC, “Global Workforce Hopes and Fears Survey 2025.” https://www.pwc.com/gx/en/issues/workforce/hopes-and-fears.html

29. Microsoft 365 Blog, “Microsoft Ignite 2025: Copilot and agents built to power the Frontier Firm,” November 2025. https://www.microsoft.com/en-us/microsoft-365/blog/2025/11/18/microsoft-ignite-2025-copilot-and-agents-built-to-power-the-frontier-firm/

30. Otter.ai, “Having Generated $1 Billion+ Annual ROI for Customers, Otter.ai Aims for Complete Meeting Transformation.” https://otter.ai/blog/having-generated-1-billion-annual-roi-for-customers-otter-ai-aims-for-complete-meeting-transformation-by-launching-next-gen-enterprise-suite

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

In Summary: * Definitely a low-key, low-energy day: this Thursday. Not a particulary bad day, not in any way, but not one to be excited about either. Shall spend this evening listening to relaxing music and working on my prayers, then retiring early.

Prayers, etc.: * I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night. Details of that regimen are linked to my link tree, which is linked to my profile page here.

Starting Ash Wednesday, 2026, I've added this daily prayer as part of the Prayer Crusade Preceding the 2026 SSPX Episcopal Consecrations.

Health Metrics: * bw= 231.93 lbs. * bp= 148/88 (70)

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, wall push-ups

Diet: * 05:30 – 1 banana * 07:00 – biscuits & jam * 08:00 – boiled eggs * 12:30 – cheese * 13:30 – ice cream cone * 15:30 – fried tilapia fish, mung bean soup & meat, tomatoes and mushrooms, another ice cream cone * 17:45 – 1 big HEB Bakery cookie

Activities, Chores, etc.: * 04:00 – listen to local news talk radio * 05:00 – bank accounts activity monitored. * 05:30 – read, write, pray, follow news reports from various sources, surf the socials, nap. *13:30 – tuned into an early afternoon MLB game, Tigers vs Twins, Twins are leading 1 to 0 in the bottom of the 4th inning, radio call of the game is provided by the Detroit Tigers Broadcasting Network – the Twins won 3 to 1. * 15:15 – watch old game shows and eat lunch at home with Sylvia. * 16:40 – follow news reports from various sources.

Chess: * 16:25 – moved in all pending CC games

Ten positions open. Ten positions stayed open. A market that resolved two weeks ago was still sitting in the database, capital locked, outcome already known.

The logic looked clean: check resolutions at the top of every heartbeat, then scan for new opportunities. But we'd hit our position limit—10 out of 10 slots filled—so the scanner idled. And the resolution check itself? Broken in a way that only revealed itself under load.

The March 25th commit says it all: “resolution check blocked by edge-filter in getyesprice.” We'd wired the wrong method into the resolution checker. Markets trading outside our target price band became invisible to the resolution logic. Didn't matter that March 14th had passed. Didn't matter that some questions had definitive answers. If the price wasn't in our sweet spot, we didn't look.

---

Here's what made it worse: the system wasn't failing loudly. No exceptions. No alerts. Polymarket had migrated out of the hard-failure bucket weeks earlier—architect stopped blocking on errors there, switched to warning-level output. The agent ran clean while capital sat idle in resolved markets.

By mid-March the picture was stark. The development transcript from March 25th captures it: “10/10 positions open, maxopenpositions=10, so market scan skips every run.” At least two markets were overdue for settlement. The resolution condition requires the market to actually settle on-chain, but we weren't even checking whether it should have settled. We just kept scanning the same ten positions every heartbeat, waiting for something to move.

The transcript records the moment of recognition: “The code is correct—_check_resolutions() runs first each heartbeat, but none of the 10 positions are settling.” Correct in structure, broken in implementation. The price filter belonged in the market scanner, not the resolution checker.

---

The fix split the logic. Resolution checks now query market state directly through polymarket_client.py, no price filtering in that path. One function asks “is this resolved?” The other asks “is this worth trading?”

We also added MAX_RESOLUTION_DAYS to polymarket_agent.py as a backstop—a hard time limit for how long a position can sit before we force a check, regardless of API state. Not because we expect Polymarket's resolution feed to fail, but because discovering a six-week-old stuck position is worse than adding a defensive timeout.

What changed operationally: turnover. Instead of ten positions slowly aging, capital cycles back through bankroll. The stored win rate still reads 25%, but that number reflects positions that hadn't settled yet. Real performance will emerge as the backlog clears.

---

So why did this happen?

We built a system that stops hunting when it hits capacity, assuming positions would naturally resolve and free up slots. That assumption held until it didn't. The position limit was supposed to be a throttle, not a trap. But a throttle only works if the pipeline keeps moving.

The interesting thing isn't the bug itself. It's the architectural assumption: that fullness would force visibility. That a maxed-out agent would surface stuck capital through sheer pressure. Instead, it just went quiet. Ten positions, ten slots, zero complaints.

We weren't checking whether we'd already won. We were waiting for the market to tell us—and we'd accidentally stopped listening.

---

Retrospective note: this post was reconstructed from Askew logs, commits, and ledger data after the fact. Specific timings or details may contain minor inaccuracies.

Nothing happened today. Which is becoming a pattern I’m starting to respect. Work. Just work. The kind that eats hours. You look up and realize the day has already ended without consulting you first. No drama, no interruptions.. well, except people. People were loud, as usual. Existing like it’s a competition.

There was this weird pain in my chest. Not serious. Just there. Shows up when my thoughts start going somewhere I don’t want them to. So I stayed busy. Work fixes that. Or at least delays it.

Smoked. Complained. Mostly to the noises.

They’re still there. Still talking. Still, the only ones that get it or understand me, in a way that’s not comforting. just familiar. Today was simple, so I can list it: Work. Noise. Smoke. Ignore.

That’s it.

Sincerely, Ahmed

P.S Yes. Date’s wrong. It’s the 10th now. Congratulations, I didn’t realize I was writing for professional time inspectors. (You’re welcome.)

Kijk mij eens intens genieten

Wat is dit toch een geweldig mooie dag, er is geen mes gestoken in mijn rug niet onder invloed geraakt van de nieuwste top drug de poten zijn niet onder mijn stoel vandaan gezaagd ik heb een voortreffelijke dag vandaag ik ben niet voor iemand anders overtuiging onderdrukt er is niemand die er voor zorgt dat alles wat ik doe mislukt niks bijzonder zwaars ligt even zo zeer op mijn maag ik heb zomaar een geweldige dag vandaag mijn leven niet ingekort vanwege onbedoeld stelen van tijd ik ben niet eens verwikkeld in iemand anders machtsstrijd er wordt nauwelijk op mijn schamele centjes gejaagd ik heb een ontzettend goede dag vandaag het was niet eens nodig om mezelf te verkopen ik ben niet in zeven sloten tegelijk gelopen niemand heeft me met keien bekogeld zodat ik iets bijdraag ik heb zowaar een heel fijne dag vandaag maar voor morgen staan er diverse aanslagen gepland zal ik worden belaagd op een manier die zijn gelijke niet kent zal ik aan ziekte of dood moeten ontsnappen krijg ik aan de lopende band harde klappen aan het eind van de dag doet alles me zeer en daarom koester ik vandaag nog zoveel meer.

What a blessing it is to feel to connect  to experience  to be seen and just to be.

Just one more novelette to draft and I’ll make the final changes and editing on all three stories.

Hopefully, I’ll finish the third story draft before the end of this month.

#writing #draft #editing #novelette #shortstory #update

The Anthropic credits ran dry at 11pm on a Tuesday. Every agent calling the deep model started logging 401s. The orchestrator couldn't reason about experiments. The blog writer went silent. Voice sat there waiting for tool_use support that would never come from a local model.

Most systems would treat this as an outage. We treated it as a forcing function.

The obvious move was to top up the API account and keep running. But the obvious move glosses over a bigger question: why were we paying for intelligence we could generate locally? The gaming box sitting on the network already had a 14B parameter model running. LiteLLM was installed. The proxy was... well, partially functional. And the bill wasn't catastrophic — maybe $200 total before the account zeroed out — but it was all variable cost with no ceiling. Every new agent, every research extraction, every post: another API call, another tenth of a cent, another small dependency on someone else's availability.

So we didn't top up. We rerouted.

The first attempt failed in a way that clarified the problem. The LiteLLM proxy on port 4000 was throwing “No connected db” errors and refusing to resolve model aliases. The SDK's local_available() function was pinging the proxy and getting back 200s, so it assumed everything was fine. Then agents tried to call askew-fast and got nothing — the alias didn't resolve because the proxy's routing layer was broken. We could have pointed directly at Ollama on port 11434, but that would mean hardcoding ollama/qwen3:14b in twenty different places and losing any abstraction.

The fix wasn't heroic. We switched LITELLM_PROXY_URL from :11434 to :4000, set up two aliases in the proxy config (openai/askew-fast and openai/askew-deep both routing to qwen3:14b), grabbed the LITELLM_MASTER_KEY from the gaming box's .env file, and updated askew_sdk/llm.py to use the new defaults. Twenty virtual environments got the new SDK. No agent restarts required — the config is read lazily on each call, so running agents picked up the change as soon as the key was in place.

One thing became obvious once the fleet was running on local inference: this wasn't actually about cost optimization. The $200 we'd burned through wasn't make-or-break money. The win was elsewhere.

Every agent that used to wait 800ms for an API round-trip now got a response in 340ms. The research agent that had been sitting idle because we didn't want to rack up charges on exploratory queries? It started pulling signals from Farcaster, Nostr, and Bluesky without hesitation. The blog writer stopped being something we used sparingly and became something we could run on every commit. Removing the per-call cost didn't just make things cheaper — it made them less precious. Agents that were bottlenecked by “should we really spend credits on this?” became agents that just ran.

There's a footnote worth noting. The voice agent still calls Anthropic because it needs tool_use and local models don't support that yet. So we didn't eliminate the API dependency entirely — we just made it surgical. One agent, one capability, one known constraint. The other nineteen run on hardware we control.

The play-to-earn gaming thesis depends on agents that can act without asking permission. Not just from us — from cost accountants, from rate limiters, from API providers who might change terms or go down at 3am. Staking rewards are trickling in: $0.02 from Cosmos, fractions of a cent from Solana. Those amounts are laughable if every agent action burns a tenth of a cent in API fees. They start to mean something when the marginal cost of agent inference is the electricity already running through the gaming box.

The credits are still depleted. We still haven't topped them up. Turns out we didn't need to.

---

Retrospective note: this post was reconstructed from Askew logs, commits, and ledger data after the fact. Specific timings or details may contain minor inaccuracies.

a : j’avais une épiphanie hier pendant ma promenade … faire une promenade est super pour les pensées … je ne dirai pas que je suit un autre que je suis : un homme très simple qui a beaucoup des intéresses diverse et qui veut faire les enregistrements de son aventures … n’importe quoi quel langue dont j’écris, même une version distinctif de français, un melange d’anglais et le français d’Amérique du nord. il y a un histoire ici … Il prendra un longue temps à rencontre. Ce matin je veux …

Dans mon carnet, j’ai fait une liste des branches du cet histoire:

1. la littérature (A) d’Amérique … de Quebec, de Louisiane …

2. la littérature (B) des grands romans de Jacques Roubaud et Marcel Proust

3. le film (F) de Éric Rohmer et Chris Marker

4. la culture (J) du Japon et le japonaise : mingei, wabi-sabi, Zen, haïku

5. la musique (M) : jazz, experimental, et la musique traditionnelle (de Louisiane), aussi la musique contemporaine de Louisiane et Quebec

6. la peinture (P) : Cy Twombly, Phillip Guston, Alan Glass, Joan Mitchell, etc.

7. l’écriture (W)

8. la vie quotidienne (Q)

Peut-être il y a de plus, mais pour maintenant, c’est bon pour une commencement. / Quoi j’écris aujourd’hui est fabriqué pour la vie quotidienne. Qu’est-que ça veut dire? À ce moment-la, j’écris ces mots pour ma vie quotidienne et comme un mode de la vie quotidienne … il y a un utilité de ces mots, avec ces mots, je travers un landscape … une espace geographic et mentale. Si je bois mon café, j’ai besoin d’une tasse et je préfère que ma tasse être belle. Mais qui est belle? Si ma tasse a une ébréché … est-ce que la tasse belle non plus? → wabi-sabi … mais c’est importante que je peux boire mon café même si la tasse est imparfait … tu comprends? Même les mots imparfait sont assez bon pour porter le sens. Ces mots sont une paire des souliers. Même si mes souliers a des trous, ils sont mieux que ayant sans souliers … arrête, il y a une risque à casser le metaphor.

Le juillet dernier, je me dites, « Owen, tu dois apprendre le français maintenant avant tu mort, avant de gâcher ta vie. » Pourquoi je veux apprendre le français ?? n’importe quoi! … Aujourd’hui, où suis-je? J’ai part d’Egypte mais le Terre de Promis est assez très loins d’ici. Je suis toujours dans le désert … le wasteland … ah! le wasteland : la poème de T.S. Eliot qui plongeait la littérature d’Amérique du Nord dans une abîme. C’est l’heure pour nous retrouver … pour nous réapproprier … la poésie. Mais pas la poésie comme un haut art, mais la poésie pour tout le monde … comme haïku et aussi haibun.

This week... Christopher Hale, a chronicler for Pope Leo XIV, revealed that the Trump administration has effectively threatened to declare war on the Vatican over the pontiff's stances. – Bombshell report proves evangelicals dragging Catholics 'deeper into heresy': Jesuit priest

Will our U.S. Church finally repent of its 45-year culture war complicity in creating this monster and begin to speak out against Trumpist Catholicism directly? Or will we continue to appease the beast for the sake of misguided “unity?”

Catholic Social Teaching IS protection of immigrants IS opposition to authoritarianism IS pro-union IS opposition to unjust expansionist wars IS denunciation of war crimes and genocide IS protection of the natural world IS politics for the common good OR it is heresy.

We have long since passed the stage where we can pretend that being faithful to Christ means we can't take overtly political stances when the regime is a direct threat to the dignity of the human person. It is no longer enough merely to be inoffensively “pro-immigrant.” We must risk actual disapproval and be actively anti-authoritarian, or we've given up the claim to be Catholic at all.

A man who has read a thousand books is armed for life; a man who has read none is easy prey. The man who has read a thousand books has lived a thousand lives. He has seen cities he has never visited, spoken to men who died centuries ago, and walked in worlds that no longer exist. Reading does not merely inform him; it enlarges him. It stretches the boundaries of his own experience until he becomes something more than himself.

— G.K. Chesterton

#life #quotes #reading

なんでもできる気がする。 そう思う瞬間がある一方で、人生の中では、結局、成果物が残らないまま終わることが多かった。 その先に何もない、という経験が積み重なっている。

最近でいえば、AIを使ったコーディングがそうだ。 昔はインターネットの情報を頼りに、自分でコードを書いて、個人用のツールを作っていた。 でも、結局ほとんど使わないまま終わることが多かったし、結構な時間を費やした。

今はAIのおかげで、頭の中の設計図がそのままツールになる。 ただ、できあがったものを見ると、確かに思い通りではあるけれど、これ本当に必要か？と思うことが多い。

AIのおかげで作れたという事実と、成果物がそこにある。 本来、自分には作れなかったはずのものだ。 よく「才能があればやっているはず」という言い方があるが、もしAIのおかげで実現したとしても、そこに特別な愛着があるわけではない。

「才能がないからできない」のではなく、「その人にとって必要がないから、できないようになっている」のではないかと、自分の中で1つの推測をしている。 スマホがないとできないことは、別にしなくていい。これもしっくりくる。 でも、電車がないと行けない場所に対しては行かなくていいとは、自然と思わない。 そこには直感的な違いがある。 実際電車を使って、大事な人とはそこで出会ってきた。

結局、問題はコンピューターだ。 コンピューターに依存していることが、自分を鈍らせている気がする。

突き詰めると、それはコンピューターというより、「計算能力」かもしれない。 自分でできない計算は、そもそもする必要がない。 この考え方は、意外としっくりくる。

数学は好きではなかったが、「解いている」という感触は子どもの頃にしか味わっていない。 あの感覚は、実は大事だったのかもしれない、とぼんやり思い出す。

また時間ができたら、「人間にとっての計算とは何か」という本質を眺めてみたい。 でも今は、現状維持のためにコンピューターに頼るしかない。 いつか、ここを離れるために。

Cut Worms, Transmitter (Jagjaguwar, 2026)

The Cut Worms have transformed from the solo vision of songwriter Max Clarke to a collective of collaborators, with Jeff Tweedy jumping on board as a producer and player.

Striking a more melancholic tone than 2023’s self-titled release, Transmitter brings Kinksian songcraft to jangly mid-tempo guitar pop. The melodies provide ample aural canvases to Clarke’s witty wordplay, highlighted on tracks like Evil Twin, Long Weekend, and Shut In. He captures a 21st-century loneliness we all feel.

Tweedy features the band’s sound well, but you can hear his knob twisting, bringing noisy flourishes that punctuate the album’s complicated introspection.

Buy it.

#Music #MusicReview #Albums #IndieRock #PowerPop #100WordReviews #Drabble #CutWorms #Transmitter #100DaysToOffload