I’ve always wanted to understand electronics a bit more. Mostly so I can repair them. We’ve been using a battery powered fan because we have no power to our house (intentionally, see this post here for details if you want), and the fan recently died. So I took it apart to see if I could figure anything out. With a volt meter I could see that the power was coming in under the battery connections at 20.8 volts. Inside there was a little circuit board connect to the switch with two wires going from the battery to that thing, and then from that switch board up to the motor. I tested up at the motor and there was nothing going from the switch to the motor.

The internet was just about useless for help. I couldn’t find a replacement switch + circuit board even though I had the part number. All the online sources were not giving me much to go on to repair it myself. And used broken fans to try and salvage parts were almost the same price as a new functioning one. It’s pretty lame living in a throw away culture.

So I ended up just cutting that switch out and hard wiring from battery to fan. I felt wires as it was running and nothing felt hot so it didn’t seem like any major problem. The biggest issue I have with it is that it is now on full blast when the battery is plugged in, where we like running it at about 30% speed for quietness and longer battery life. But it’s been so warm we wanted to run it and have been.

Just a warning to everyone out there who may try something like this. It turns out that the battery does not have a low voltage cutoff built into it. I ran the fan last night and it ran until it completely killed the battery. The battery was so low that it wasn’t recognized by the charger and wouldn’t charge. I found out that you can jump two batteries together by putting a wire from positive to positive and negative to negative and revive the dead battery to the point of being able to charge it again.

Here are a couple videos on the idea:

video one battery repair

video two battery repair

If you do this be careful. I noticed that the wires I used got warm. It’s better to copy the method used on video two. Touch the wires on and off to pulse some power to it rather than just hook it up and let it sit. It was hard to get wires in there, so I had to use too small of wires for the job. Doing this is risky and if you just left it there the wires could start on fire. So I only hooked it up for about 5 seconds and could feel it getting a little warm. I think it’s also smart to copy the method in video one where he’s using the same kind of battery to jump the dead one if you can. When I pushed the button on the battery to see how much power was left, it still did not register – the battery was still pretty low. But when I plugged it into the charger it worked! So now it’s out there charging.

If I use the fan anymore I’ll be monitoring the battery level more regularly. If you run batteries to very low voltage (beyond what it is built to do) you can do permanent damage. I may have shortened the lifespan by doing all this. However it’s an older battery and overall I’ve learned a lot through this.

If you think your battery is dead because it was over-drained for whatever reason you may be able to revive it without any specialized “smart charger.” One reason would be if you left a very low battery uncharged somewhere for too long and then came back to it thinking it was completely dead. This trick might give it a second life.

Hope this helps, have a great one!

Move along. Nothing to see here.

She is eighty-five, she lives in the United States, and every morning a small tabletop device with a swivelling head and a soft glowing base tells her it is time to take her medication. It suggests she stretch. It asks how she slept. It is called ElliQ, it is made by the Israeli company Intuition Robotics, and according to the opinion piece that opened with her story in the Korea Times on 19 August 2026, it helps her stay independent.

The author of that piece was Suh Chung-ha, a former Korean ambassador to Singapore and Hungary who now runs the ASEM Global Ageing Center in Seoul. His argument was not that the robot is bad. His argument was subtler and considerably more uncomfortable: that the same broad technological shift that produced her helpful companion is quietly reshaping her access to healthcare, long-term care, credit, insurance and public services, and that it is doing so using systems trained on data which encode decades of assumptions about what old people are worth.

Here is the thing that should keep you awake. There are two artificial intelligence systems in this woman's life. One of them sits on her side table, greets her by name, and was designed with people like her explicitly in mind. The other one has never been in her house, has no name, no face and no voice, and it is scoring her.

She chose the first. The second chose her.

Two Machines, One Household

The asymmetry is almost perfectly clean, and it is worth stating precisely because it is the structural fact from which nearly everything else in this story follows.

The assistive machine is opted into. It arrives through a screening process, in the New York State case run by county and locality-based Area Agencies on Aging. It is visible: it occupies physical space, it announces itself, it is marketed at older people as a product for older people. If she hates it, she can unplug it and someone will come and take it away.

The discriminatory machine has none of these properties. She did not opt into the underwriting model that prices her travel insurance, the credit decisioning system that assessed her application for a modest overdraft extension, or the triage algorithm that sorted her referral. She cannot see them. She was not consulted in their design, and neither was anyone remotely like her. She cannot unplug them. In most cases she will never learn that a model was involved at all; she will simply receive an outcome, in a letter or on a screen, expressed in the passive voice.

Assistive AI for older people is a market with a sales pitch. Decisional AI about older people is infrastructure with a legal department.

Public debate about AI and ageing has been overwhelmingly captured by the first category. Companion robots photograph well. They allow governments with ageing populations and inadequate care workforces to point at something tangible. Meanwhile the systems that will actually determine whether an eighty-five-year-old can borrow money, buy cover for a trip to see her grandchildren, or get onto a surgical waiting list are being deployed with almost no public conversation about age at all.

Ninety-Five Per Cent of What, Exactly

Start with the good machine, because the claims made for it deserve the same scepticism we would apply to anything else.

In August 2023 the New York State Office for the Aging announced that its ElliQ rollout had produced a 95 per cent reduction in loneliness among participants. The figure travelled fast, and has been repeated in trade press, vendor materials and policy briefings ever since. That 2023 release reported that more than 800 older New Yorkers were in the programme, that users interacted with the device more than thirty times a day, six days a week, and that over 75 per cent of those interactions related to social, physical or mental wellbeing. Greg Olsen, the agency's director, said the results were “truly exceeding our expectations”.

Thirty interactions a day is not a device gathering dust.

Now read what the same agency published in February 2026. Its year-three project update, covering the programme year from June 2024 to May 2025, reports that 94 per cent of clients say they feel less lonely, up from 93 per cent the year before, that 97 per cent report feeling better overall and 79 per cent feel more connected to the world around them, with customer satisfaction at 4.6 out of 5. The average client is 75. As of May 2025, 834 older adults had joined. More than 3,500 have applied.

Four applicants for every place.

Look at what happened to the sentence. In 2023 the claim was a 95 per cent reduction in loneliness: a delta, a measured change, phrasing that implies an instrument, a baseline and a follow-up. In 2026 it is 94 per cent of clients who say they feel less lonely. That is not a reduction. It is a self-report, and the agency now presents it as one.

The wording did not soften by accident.

Neither version was ever a clinical finding. Both are programme metrics derived from participants who were screened in, who wanted the device, and who were asked how they felt. There is no control group in those numbers. There is no validated loneliness instrument named alongside them in the public materials, no randomisation, no blinding, and no comparison against the obvious alternative intervention, which is a person visiting.

Note too how little the figure moves. Ninety-three per cent, then 94, across a self-selected cohort that grew by hundreds in between. Effect estimates wander when the sample changes; satisfaction scores do not. The 4.6 out of 5 sitting in the same document is from the same family of measurement.

The wider literature is more honest and less exciting. A systematic review and meta-analysis by Lihui Pu, Wendy Moyle, Cindy Jones and Michael Todorovic, published in The Gerontologist, screened more than two thousand articles and found thirteen from eleven randomised controlled trials, nine of which entered the meta-analysis. Social robots appeared to have positive effects on agitation, anxiety and quality of life, but the meta-analysis found no statistical significance. The authors flagged a relatively high risk of bias in allocation concealment and blinding, and concluded that firm conclusions were limited by the shortage of high-quality studies. A later meta-analysis published in the Journal of the American Medical Directors Association, focused on residents of long-term care facilities and drawing on eight trials, did report significant reductions in depression and loneliness with large effect sizes.

So: promising, contested, and nowhere near the confidence implied by a round 95.

None of this means ElliQ is useless. It plainly is not; the engagement figures describe a device in near-constant use, and 834 people have one while thousands wait. It means that the most widely circulated statistic about AI and older people is a self-reported satisfaction figure from a self-selected group, and that we have collectively decided to treat it as proof of concept for an entire policy direction.

The Awkward Protected Characteristic

Now the harder half, and it requires conceding something that age-discrimination advocates often skate past.

Age is a genuinely strange thing to build fairness engineering around. Race and sex, as legal categories, are treated as characteristics that should almost never bear on how you are priced or assessed. Age is not treated that way, and not merely out of prejudice. Age correlates with mortality and morbidity in ways that are real, measurable and actuarially load-bearing. An insurer pricing life cover without reference to age is not being fair; it is being incompetent.

The law recognises this explicitly, and the contrast is sharper than most people realise.

When the Equality Act 2010 extended the ban on age discrimination to the provision of goods, facilities and services in April 2012, it carved out financial services. Schedule 3 permits providers to use age in connection with a financial service, provided that any risk assessment involving age is carried out by reference to information relevant to the assessment and from a source on which it is reasonable to rely. Insurers and banks can price by age. They just have to be able to show the evidence is relevant and the source reasonable.

Compare this with what happened to sex. In the Test-Achats case the Court of Justice of the European Union struck down Article 5(2) of the Gender Directive, the provision that had allowed insurers to differentiate by gender, ruling it incompatible with the principle of equal treatment and invalid from 21 December 2012. The wording of the age exception is close to identical to the gender exception the court destroyed. It survives anyway.

Age, in other words, occupies a legal position no other protected characteristic holds: formally protected, substantively negotiable, with a standing statutory permission to price on it as long as you can point at a table.

There is a second awkwardness. Age is continuous, not categorical. Most fairness metrics in machine learning are built for discrete groups: compare outcomes for group A against group B, measure the gap, minimise it. Continuous attributes require binning, and binning is a modelling choice that quietly determines what you will find. Is the relevant comparison 65 and over against under 65? 80 and over against everyone else? Each decade separately? A model can look admirably fair across coarse bands and be brutal at the eighty-fifth birthday.

That the technical community is working on this is not in doubt. A paper posted to arXiv on 7 April 2026 by Fernando López, Paula Delgado-Santos, Pablo Gómez, David Solans and Jordi Luque examined demographics-agnostic training for bias mitigation in wake-up word detection, evaluating fairness across sex, age and accent, and reported that one technique reduced predictive disparity by 83.65 per cent for age. Note what that result implies about the baseline. A voice interface, the very modality most often proposed as the accessible option for people who struggle with screens, had an age disparity large enough that removing four fifths of it counted as a headline.

Where the Actuarial Defence Runs Out

Take the actuarial argument seriously and it still only covers a fraction of the territory.

It works for life insurance, where the outcome predicted is death and age is causally implicated in death. It works, with more strain, for annuities and some health cover. It does not work for the vast and expanding class of decisions where age enters not as a causal variable but as a learned correlation with something the model was never asked to think about.

Consider hiring. In August 2023 the United States Equal Employment Opportunity Commission settled with the tutoring company iTutorGroup for $365,000, in what was widely described as its first settlement involving an AI-driven hiring tool. The company's application software had been configured to automatically reject female applicants aged 55 and over and male applicants aged 60 and over. More than 200 qualified applicants were rejected on that basis. The discrimination came to light in an almost novelistic way: an applicant submitted two applications identical in every respect except the date of birth, and only the younger one got an interview. The consent decree included five years of EEOC monitoring and an injunction against requesting applicants' birth dates.

There is no actuarial defence for that. It was a hard filter, and it was illegal.

The more consequential case is messier. In Mobley v. Workday, Derek Mobley alleges that the applicant screening tools supplied by Workday systematically disadvantaged older job seekers; he says he submitted more than a hundred applications through the platform and was rejected every time. Judge Rita Lin of the United States District Court for the Northern District of California dismissed his intentional discrimination claim but allowed the disparate impact allegation to proceed, and on 16 May 2025 granted preliminary certification of a nationwide collective action under the Age Discrimination in Employment Act, covering applicants aged 40 and over denied recommendations through the platform since 24 September 2020. The court had earlier accepted the theory that an AI vendor could be directly liable for employment discrimination as an “agent” of the employer, and a March 2026 ruling rejected Workday's argument that the ADEA does not cover job applicants.

Two rulings since have sharpened it, in opposite directions. On 28 May 2026 the court held that AI bias-testing data can be protected from discovery by attorney-client privilege, shielding Workday's own testing material while accepting that it had probative value as evidence of disparate impact, on the basis that counsel had been substantively involved in curating it. The most useful evidence for establishing whether a screening model disadvantages older applicants is the vendor's own bias testing, and a vendor that routes that testing through its lawyers may be able to keep it from the people the model rejected.

Then on 22 June 2026 the court granted in part and denied in part Workday's motion to dismiss. It declined to dismiss an Americans with Disabilities Act claim built on a proxy-discrimination theory, the allegation being that the screening tools inferred health status. It declined to dismiss claims under California's Fair Employment and Housing Act, finding sufficient allegations that Workday designed, developed, maintained and controlled the tools from its California headquarters. It did dismiss a Title VII race-based disparate impact claim brought by a plaintiff who had not sought authorisation to add it, and struck a newly asserted theory that Workday was itself the direct employer. The allegations remain allegations; the case is unresolved.

What makes Mobley the important one is that nobody claims a birth date field was set to reject anyone. The claim is that a model, trained on which past applicants got hired, learned the shape of the people who tend to get hired, and that this shape has an age.

That is not actuarial risk. That is a machine reproducing a hiring market's existing prejudice at industrial throughput and calling it a recommendation.

The Ghost in the Feature Set

The standard corporate response is to remove age from the model. Anyone who has worked on this knows why that fails, but the mechanism deserves spelling out, because it is where the eighty-five-year-old actually gets caught.

Age is one of the most redundantly encoded attributes in consumer data. It leaks through everything.

The landmark demonstration of how much can be inferred from almost nothing is the study by Tobias Berg, Valentin Burg, Ana Gombović and Manju Puri, published in the Review of Financial Studies, which analysed over 250,000 purchases at a German e-commerce firm. Their finding was that a handful of trivially available “digital footprint” variables matched the predictive power of a credit bureau score for consumer default. The variables were not financial. They included the device type and operating system the customer was using, characteristics of their email address, the channel through which they arrived at the site, and the time of day the order was placed.

Every one is age-correlated. Operating system and device age track purchasing power and upgrade behaviour, which skew by generation. Email domain is a near-fossil record: certain providers cluster heavily among people who set up an address in a particular decade and never changed it. Whether you arrived via a search engine, a price-comparison site or by typing the address directly is a behavioural signature that varies sharply with digital fluency. Time of day correlates with employment status and with sleep patterns that shift with age.

Add the signals a modern web session captures without asking: typing speed and correction rate, scroll behaviour, time per form field, zoom level, whether accessibility settings are enabled, session length, abandonment patterns, whether the customer switched to the telephone halfway through.

A model given these features and told to predict default, or churn, or fraud, or claim frequency, will find age whether or not you have deleted the birth date column. It will not label the pattern “age”. It will simply learn that a slow-typing user on an old Android device who zoomed the page, took eleven minutes over a form and then rang the call centre belongs to a cluster with a particular outcome rate. The cluster is old people. The model does not know this and does not need to.

This is proxy discrimination, and age is the characteristic most vulnerable to it, because unlike race or sex it is continuously written into behaviour rather than occasionally into a form field. You can decline to state your sex. You cannot decline to type at the speed you type.

It is also, since June 2026, a theory a federal court has agreed to hear. The proxy-discrimination claim that survived Workday's motion to dismiss is this argument made in a courtroom rather than a conference paper: that a system can sort people by a protected characteristic it was never given and could not name if asked.

A World Where They Were Not There

There is a deeper problem underneath the proxy problem, and it is the one the World Health Organization identified with unusual bluntness in February 2022 in its policy brief “Ageism in artificial intelligence for health”.

The brief made a point that is easy to nod along to and hard to fully absorb: the datasets used to train AI models frequently exclude older people, who often sit within a minority subset for technologies not explicitly designed as gerontechnology. It set out eight considerations, among them participatory design of AI by and with older people, age-diverse data science teams, age-inclusive data collection, investment in digital infrastructure and digital literacy for older people and their carers, rights for older people to consent and to contest, and governance frameworks with teeth.

Under-representation in training data is not neutral. This is the part that gets lost.

If a population is thinly represented in the data, the model has less signal about them, so its predictions for them are less accurate and typically more conservative. Less accurate prediction for a group means more errors in both directions, but the consequences of those errors are asymmetric. A false negative for an older applicant means a declined loan or a rejected application. A false positive means an accepted risk. Institutions tune thresholds to avoid the second kind of error, so noisier estimates for a group systematically produce more refusals for that group. Uncertainty gets priced as risk.

Now compound it across time. Because older people were less present in digital life during the decades when the training corpora were accumulating, they generated fewer digital records. Because they generated fewer records, models are worse at assessing them. Because models are worse at assessing them, they are more often refused or steered towards manual, slower, more expensive channels. Because they are pushed off the digital rails, they generate still fewer records. This is the thin-file problem, and for older people it runs in the opposite direction from the intuitive one: a person can have fifty years of impeccable financial history and still be functionally invisible to a model that mostly reads behavioural exhaust from the last eighteen months.

The past is not a neutral training set. It is a record of who was allowed to participate.

The Recursive Trap

Here is where the digital divide stops being a story about access and becomes a story about power, and it is the thread that runs directly back to the woman with the robot on her side table.

The numbers are not ambiguous. Ofcom's Adults' Media Use and Attitudes report, published on 2 April 2026, found that 6 per cent of UK adults still have no home internet access, and that 83 per cent of that group are aged 65 or over, with 66 per cent aged 75 and above. Among those offline, 68 per cent said they were not interested or felt no need, 38 per cent found it too complicated and 25 per cent cited cost. Age UK reported in July 2025 that 2.4 million older people, nearly one in five, use the internet less than once a month or not at all, that 920,000 had reduced their internet use in the previous twelve months, and that 4.3 million, a third, do not use a smartphone. Exclusion was higher among older Black people at 32 per cent and older Asian people at 26 per cent, and among older people living alone at 30 per cent. Caroline Abrahams, Charity Director at Age UK, has warned repeatedly that people who cannot or will not go online must still be able to reach services offline.

In the United States, Pew Research Center reported in January 2026, drawing on a survey conducted between February and June 2025, that 78 per cent of adults aged 65 and over own a smartphone against 97 per cent of adults under 50, that 70 per cent have home broadband, and that 14 per cent are online almost constantly compared with 63 per cent of those aged 18 to 29.

Now put those two facts side by side.

Fact one: older people are the population most likely to be scored by systems they cannot see, and most likely to be misscored because of thin data and proxy leakage. Fact two: older people are the population least equipped to use the machinery that exists for challenging an automated decision.

Because that machinery is digital. All of it. The right of appeal lives behind a login. The “why was I declined?” explanation is a link in an email. The subject access request is a web form. The complaint goes to a chatbot that triages before a human sees it. The regulator's guidance is a PDF. The decision notice arrives in an app.

Article 22 of the General Data Protection Regulation is supposed to be the backstop. It gives people the right not to be subject to a decision based solely on automated processing that produces legal or similarly significant effects, and where such decisions are permitted, Article 22(3) requires safeguards including the right to obtain human intervention, to express a point of view and to contest the decision. Legal scholars have criticised the provision for years, principally over the word “solely”, which invites institutions to insert a nominal human who rubber-stamps the model output, and over the vagueness of what counts as meaningful information about the logic involved.

But there is a failure mode more basic than any of those doctrinal complaints. A right you have to go online to exercise is not a right for someone who is not online. It is a courtesy extended to people who can already reach it.

This is the recursive trap. The people most likely to be wrongly assessed by an algorithm are, by the same underlying cause, the people least able to find out that an algorithm assessed them, least able to obtain an explanation, and least able to appeal. Digital exclusion does not merely sit alongside algorithmic harm. It is the mechanism that makes algorithmic harm unaccountable. The error and the inability to contest the error have a common origin, and that common origin is age.

What Seoul Cannot Fix by Declaration

On 2 September 2026, the ASEM Global Ageing Center will convene the 6th ASEM Forum on the Human Rights of Older Persons in Seoul, under the theme “Artificial Intelligence and the Human Rights of Older Persons: Toward Age-inclusive AI Transformation”, bringing together experts from Asia and Europe. Suh's Korea Times piece was, transparently, a curtain-raiser for it.

The forum arrives at a moment of unusual institutional motion. On 3 April 2025 the UN Human Rights Council adopted by consensus a decision to establish an intergovernmental working group to begin drafting a legally binding convention on the human rights of older persons, after more than a decade of stalled effort in the open-ended working group on ageing. The new body held an organisational meeting in Geneva in February 2026, convened its first substantive session from 13 to 17 July 2026, and will hold its second session from 26 to 30 October 2026 at the Palais des Nations in Geneva, with the early sessions devoted to purpose, general principles and scope before any drafting of articles. The timetable beyond that is now known: a discussion of an outline of the convention's main elements is expected in July 2027, and a first zero draft around October 2027. The International Telecommunication Union published its own report in July 2026 on artificial intelligence and ageing, examining the unequal distribution of AI benefits across age, gender and region.

This is real progress and it will take years. An outline of main elements in mid-2027, a zero draft in late 2027, and then the negotiation of text that states have to agree, sign and ratify before it binds anyone. The woman in the opening paragraph is eighty-five now.

Meanwhile, the regulation that already exists treats age oddly. The EU AI Act prohibits, under Article 5(1)(b), AI systems that exploit vulnerabilities due to age, disability or specific socio-economic circumstances in order to materially distort behaviour, with those prohibitions applicable from 2 February 2025. That is a genuine protection against the payday-lender-targeting-the-cognitively-impaired scenario. It is not a protection against underwriting. Credit scoring and life and health insurance pricing sit in the high-risk category under Annex III, which brings documentation, data governance and human oversight duties, but lawful risk assessment carried out for legitimate purposes with proportionate safeguards falls outside the Article 5 prohibition. Which is to say: the Act catches predation and regulates underwriting, but it does not question whether age-based underwriting is itself the problem, because European law has already decided that it is not.

The American position is different and, in its way, weaker. The Age Discrimination in Employment Act of 1967 covers employment and does so reasonably robustly, as Mobley is testing. Outside employment, there is no federal equivalent of the Equality Act's general services provision. The Equal Credit Opportunity Act does prohibit age discrimination in credit transactions, and Regulation B is on its face protective: a creditor may use age as a predictive variable in an empirically derived, demonstrably and statistically sound scoring system, but only provided the age of an elderly applicant is not assigned a negative factor or value, and applicants aged 62 and over must be treated at least as favourably as those under 62. Read that carefully and you can see exactly where it fails. The rule polices the explicit age variable. It says nothing about a model that has never seen a date of birth and has inferred one from an operating system, a typing cadence and an email domain. You cannot audit for a negative factor assigned to elderly applicants if the model does not know which applicants are elderly, and neither, formally, does the institution running it.

Conference declarations do not touch any of this. The gap between what Seoul will resolve and what a German e-commerce model does with an old Android handset is the whole subject.

Four Things That Would Actually Change the Arithmetic

Strip away the declaratory language and there are perhaps four interventions that would materially alter the position of the woman in the opening scene. None of them are technically hard. All of them are expensive, which is why they have not happened.

The first is a legally enforceable right to a non-digital channel. Not a helpline that exists at the discretion of the provider, not a branch that survives until the next cost review, but a statutory obligation on any organisation providing an essential service to maintain a route to a competent human being that requires no internet connection, no smartphone and no app. Age UK has been arguing this for years, most pointedly in its work on the collapse of high street banking, where the shift to online-only services has left people who do not trust or cannot use digital channels struggling to manage their own money. Offline access is currently a courtesy. It needs to be a licence condition.

The second is age-disaggregated auditing as a compliance requirement rather than a research exercise. Institutions deploying models in credit, insurance, employment and healthcare triage should be required to publish outcome rates by fine-grained age band, not by a single crude over-65 bucket that conceals everything interesting, and to do so alongside approval rates, appeal rates and appeal success rates. You cannot regulate a disparity that nobody has to measure.

The third is co-design that is not decorative. The WHO brief called for participatory design by and with older people and for age-diverse data science teams, which sounds like boilerplate until you consider how few people building consumer risk models have ever watched an eighty-five-year-old complete an online form.

The fourth is human review that is genuinely reachable and genuinely empowered: a named person, contactable by telephone, with the authority and the information to overturn a model, and a duty to record why. Article 22 gestures at this. Nobody has made it real.

The Grandchild That Isn't

Return, finally, to the room with the robot in it, because there is a question underneath the discrimination question that the fairness metrics cannot reach.

Sherry Turkle, the MIT professor who has spent decades studying what happens to people around machines, argued in Alone Together that sociable technology “will always disappoint because it promises what it cannot deliver. It promises friendship but can only deliver performances.” Her worry was never that robots do things for us. It was that they do things to us: that we attach to what we nurture, and that outsourcing the nurturing dissolves the attachment.

Recent research suggests this is not merely philosophical. A study posted to arXiv on 26 February 2026 by Tianqi Song, Black Sun, Jingshu Li, Han Li, Chi-Lan Yang, Yijia Xu and Yi-Chieh Lee examined AI-generated influencers on Chinese short-video platforms that adopt kinship personas, presenting themselves as virtual grandchildren, using visual and conversational cues to enact family roles. Through social media analysis and interviews with older adults, the researchers found that these relationships met real informational and emotional needs, and also identified risks including emotional displacement and unequal emotional investment.

Unequal emotional investment. That phrase should be read slowly. It describes a relationship in which one party gives everything and the other party is a product roadmap.

The care-substitution risk is not that a family decides to buy a robot instead of visiting. It is subtler and more institutional. It is that a care system under fiscal pressure, looking at a 95 per cent loneliness reduction figure and a device that costs a fraction of a support worker's hourly rate, makes an entirely rational commissioning decision. Nobody need intend the substitution for it to happen. It is a budget line, not a betrayal.

The Bill Arrives in the Post

So here she is, eighty-five years old, at the intersection of both machines.

The one on her side table knows her medication schedule, notices when she has not moved for a while, and asks about her day. It has probably improved her life; the engagement data suggests she uses it constantly. It was designed for her, sold to a state agency on her behalf, and screened to her through a public programme.

The other one does not know she exists as a person. It knows a vector: an operating system four versions behind, a form completion time in the ninety-ninth percentile, an email domain that has not been fashionable since the Clinton administration, a preference for the telephone channel, a session at three in the afternoon. It has never been told her age. It does not need to be told her age. It has learned the residue that age leaves on everything a person touches, and it has priced it.

When it declines her, or loads her premium, or drops her below a referral threshold, the letter will not say why. If she wants to know why, she will be directed to a portal. If she cannot use the portal, she will be offered a chatbot. If the chatbot cannot help, she will be given a number that leads to a menu. And at the end of that process, if she reaches it, a human being will look at a screen showing the model's output and a confidence score, and will decline to overturn it, because overturning it requires a reason and the reason is buried in a feature interaction that nobody at the institution can articulate either.

And if anyone ever tested the model for age bias, the test may be privileged.

Suh's article carried the line that no one should be considered too old for AI. It is a good line. But the more precise formulation of the problem is that nobody is too old for AI, because AI does not require your participation. It requires only your data exhaust, and it will make decisions about your money, your health and your access to public life whether or not you have ever touched a keyboard.

The robot on the side table is the part of this she agreed to. Everything else is happening to her, in rooms she will never see, in a language nobody will translate, on the basis of a life lived mostly before the data started being collected.

Sources and References

1. Suh Chung-ha (2026) “No one should be too old for AI,” The Korea Times, 19 August 2026. Available at: https://www.koreatimes.co.kr/opinion/20260819/no-one-should-be-too-old-for-ai
2. World Health Organization (2022) Ageism in artificial intelligence for health: WHO policy brief, WHO, 9 February 2022, ISBN 978-92-4-004079-3. Available at: https://www.who.int/publications/i/item/9789240040793
3. New York State Office for the Aging (2023) “NYSOFA's Rollout of AI Companion Robot ElliQ Shows 95% Reduction in Loneliness,” press release, 1 August 2023. Available at: https://aging.ny.gov/news/nysofas-rollout-ai-companion-robot-elliq-shows-95-reduction-loneliness
4. New York State Office for the Aging (2026) Transforming Care for Older Adults Across the State of New York: ElliQ Project Update, February 2026. Available at: https://aging.ny.gov/system/files/documents/2026/02/nysofa-elliq-project-update-2026.pdf
5. Pu, Lihui, Moyle, Wendy, Jones, Cindy and Todorovic, Michael (2019) “The Effectiveness of Social Robots for Older Adults: A Systematic Review and Meta-Analysis of Randomized Controlled Studies,” The Gerontologist, 59(1), pp. e37-e51. Available at: https://academic.oup.com/gerontologist/article/59/1/e37/5036100
6. Yen, Hsin-Yen, Huang, Chia-Wei, Chiu, Hsiao-Ling and Jin, Gaoxiang (2024) “The Effect of Social Robots on Depression and Loneliness for Older Residents in Long-Term Care Facilities: A Meta-Analysis of Randomized Controlled Trials,” Journal of the American Medical Directors Association, 25(6), 104979. Available at: https://www.jamda.com/article/S1525-8610(24)00176-2/fulltext
7. U.S. Equal Employment Opportunity Commission (2023) “iTutorGroup to Pay $365,000 to Settle EEOC Discriminatory Hiring Suit,” press release, 9 August 2023. Available at: https://www.eeoc.gov/newsroom/itutorgroup-pay-365000-settle-eeoc-discriminatory-hiring-suit
8. Holland & Knight (2025) “Federal Court Allows Collective Action Lawsuit Over Alleged AI Hiring Bias,” Insights, May 2025. Available at: https://www.hklaw.com/en/insights/publications/2025/05/federal-court-allows-collective-action-lawsuit-over-alleged
9. Duane Morris Class Action Defense (2026) “California Federal Court Grants In Part And Denies In Part Workday's Motion To Dismiss In Mobley v. Workday,” 24 June 2026. Available at: https://blogs.duanemorris.com/classactiondefense/2026/06/24/california-federal-court-grants-in-part-and-denies-in-part-workdays-motion-to-dismiss-in-mobley-v-workday/
10. Norton Rose Fulbright (2026) “Behind the privilege shield: Safeguarding AI bias-testing data in employment decisions,” Inside Tech Law, June 2026. Available at: https://www.insidetechlaw.com/blog/2026/06/behind-the-privilege-shield-safeguarding-ai-bias-testing-data-in-employment-decisions
11. Berg, Tobias, Burg, Valentin, Gombović, Ana and Puri, Manju (2020) “On the Rise of FinTechs: Credit Scoring Using Digital Footprints,” The Review of Financial Studies, 33(7), pp. 2845-2897. Available at: https://academic.oup.com/rfs/article-abstract/33/7/2845/5568311
12. Pinsent Masons (2024) “Age discrimination and insurance,” Out-Law Guide. Available at: https://www.pinsentmasons.com/out-law/guides/age-discrimination-and-insurance
13. UK Government (2012) The Equality Act 2010 (Amendment) Regulations 2012, SI 2012/2992, legislation.gov.uk. Available at: https://www.legislation.gov.uk/uksi/2012/2992/made
14. Information Commissioner's Office (2026) “Rights related to automated decision making including profiling,” UK GDPR Guidance and Resources. Available at: https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/individual-rights/individual-rights/rights-related-to-automated-decision-making-including-profiling/
15. European Union (2024) “Article 5: Prohibited AI Practices,” Regulation (EU) 2024/1689 (Artificial Intelligence Act). Available at: https://artificialintelligenceact.eu/article/5/
16. Ofcom (2026) Adults' Media Use and Attitudes Report 2026, published 2 April 2026. Available at: https://www.ofcom.org.uk/siteassets/resources/documents/research-and-data/media-literacy-research/adults/adults-media-use-and-attitudes-2026/adults-media-use-and-attitudes-2026-report.pdf
17. Age UK (2025) “Age UK warns 2.4 million digitally excluded older people are at risk of being left behind in an increasingly digital world,” press release, 29 July 2025. Available at: https://www.ageuk.org.uk/latest-press/articles/age-uk-warns-22.4-million-digitally-excluded-older-people-are-at-risk-of-being-left-behind-in-an-increasingly-digital-world/
18. Age UK (2023) “You can't bank on it anymore”: The impact of the rise of online banking on older people, May 2023. Available at: https://www.ageuk.org.uk/siteassets/documents/reports-and-publications/reports-and-briefings/money-matters/the-impact-of-the-rise-of-online-banking-on-older-people-may-2023.pdf
19. Pew Research Center (2026) “Internet use, smartphone ownership, digital divides in the US: What we know,” Short Reads, 8 January 2026. Available at: https://www.pewresearch.org/short-reads/2026/01/08/internet-use-smartphone-ownership-digital-divides-in-u-s/
20. Office of the High Commissioner for Human Rights (2026) “Second session of the Intergovernmental Working Group on the human rights of Older Persons, 26-30 October 2026,” OHCHR. Available at: https://www.ohchr.org/en/events/sessions/2026/second-session-intergovernmental-working-group-human-rights-older-persons-26
21. International Telecommunication Union (2026) Artificial intelligence and ageing: Inclusive pathways for older persons in a digital world, ITU, July 2026. Available at: https://www.itu.int/hub/publication/d-phcb-ai_age-2026/
22. Song, Tianqi, Sun, Black, Li, Jingshu, Li, Han, Yang, Chi-Lan, Xu, Yijia and Lee, Yi-Chieh (2026) “Understanding Older Adults' Experiences of Support, Concerns, and Risks from Kinship-Role AI-Generated Influencers,” arXiv preprint 2602.22993, 26 February 2026. Available at: https://arxiv.org/abs/2602.22993
23. López, Fernando, Delgado-Santos, Paula, Gómez, Pablo, Solans, David and Luque, Jordi (2026) “'OK Aura, Be Fair With Me': Demographics-Agnostic Training for Bias Mitigation in Wake-up Word Detection,” arXiv preprint 2604.05830, 7 April 2026. Available at: https://arxiv.org/abs/2604.05830
24. Turkle, Sherry (2011) Alone Together: Why We Expect More from Technology and Less from Each Other, Basic Books, New York.
25. Consumer Financial Protection Bureau (2026) “12 CFR § 1002.6 Rules concerning evaluation of applications,” Regulation B (Equal Credit Opportunity Act), eCFR. Available at: https://www.ecfr.gov/current/title-12/chapter-X/part-1002/subpart-A/section-1002.6

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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

Listen to the free weekly SmarterArticles Podcast

In Summary: * After having received injections in both eyeballs this afternoon for my wet macular degeneration condition, I've spent several hours barely able to see. At least I can still hear well enough to enjoy my MLB game tonight. And I'm confident my vision will be back to my normal when I wake up tomorrow morning.

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.

Health Metrics: * bw= 224.87 lbs. * bp= 131/80 (68)

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

Diet: * 04:55 – 1 banana, 1 little cupcake * 08:00 – pizza * 18:00 – garden salad

Activities, Chores, etc.: * 04:10 – listen to local news talk radio * 04:35 – bank accounts activity monitored . * 05:00 – read, write, pray, follow news reports from various sources, surf the socials, nap * 12:30 – Go to Retina Doc appointment * 16:30 – home from the Retina Doc. After having received injections in both eyeballs, can still barely see * 18:00 – tuned into 105.3 The Fan ahead of tonight's Rangers / White Sox game.

Chess: * 09:00 – moved in all pending CC games

Chapter 1: When You Realize You May Not Be Seeing Clearly

You can sit with an open Bible in front of you and still feel unsettled by a passage you have read before. Maybe it happens late at night, after the house is quiet, when you are too tired to pretend you have everything figured out. You read Mark 8 and stop at the blind man because something about his healing does not fit the neat picture in your head. If you have ever wanted to watch why Jesus healed the blind man twice in Mark 8, you are not alone. The story is brief, but the question stays with you.

The man is brought to Jesus by people who want him healed. Jesus takes him by the hand, leads him outside the village, and begins the healing in a way that feels strange to us. After the first touch, the man can see, but not clearly. People look like trees walking around. Then Jesus touches him again, and his sight becomes clear. It belongs beside a deeper reflection on what it means to see Jesus clearly, because the real tension may not be about whether Jesus had enough power the first time.

Think about how unsettling it is to discover that you have misunderstood something important. A father may believe his teenage son is becoming distant because he does not care, only to learn that the boy has been afraid to admit he is struggling. We can look directly at someone, hear their words, and still fail to understand what is happening inside them. Seeing something is not always the same as seeing it clearly.

That is what makes this miracle feel so personal. The man is no longer blind after the first touch, but neither is his vision complete. He is somewhere in between. Most of us dislike that middle place. We want faith to feel settled. We want our understanding of Jesus to be finished. We want to know that what we believe today will never need to be corrected tomorrow.

Yet the disciples were already close to Jesus when they faced this same problem. They had heard His teaching, watched His miracles, and traveled beside Him. Just before this healing, Jesus asked whether they had eyes but still failed to see. He was speaking to people who were already following Him.

That is the quiet challenge in Mark 8. You can love Jesus sincerely and still carry assumptions about Him that need to change. You can believe and still misunderstand. You can be faithful and still discover that something you considered clear was only partial sight. Spiritual growth may sometimes begin with a harder prayer than asking Jesus to show us something new. It may begin when we ask Him to show us where we have been looking at Him for years and still have not seen Him clearly.

Chapter 2: When Faith Has to Survive the Middle

A woman sits in her car outside a grocery store with the engine off and both hands resting on the steering wheel. She has prayed about the same family problem for months. Some things have improved, but not enough for her to call it resolved. She can point to small signs of hope, yet she still does not know where the situation is going. That uncomfortable space between nothing changing and everything being restored can feel a lot like the blind man standing before Jesus after the first touch.

He was not where he had been, but he was not yet where he wanted to be.

That part of the story matters because many of us live much of our faith in the middle. We have seen enough of Jesus to trust Him, but we still have questions. We have experienced answers to prayer, but other prayers remain open. We have grown, but there are still habits, fears, assumptions, and wounds that distort what we see.

We sometimes treat uncertainty as evidence that something is wrong with our faith. Mark 8 suggests something more patient. The man's incomplete sight was not the end of his encounter with Jesus. Jesus did not abandon him because the first moment left him seeing imperfectly. He stayed with him.

That can change the way we think about our own unfinished places.

Maybe you understand forgiveness better than you used to, but there is still one person whose name changes the atmosphere inside you. Maybe you believe God is trustworthy, yet financial pressure makes you check your bank account three times before bed. Maybe you know Jesus tells you not to live in fear, but a medical test is coming and your mind keeps traveling toward the worst possible result.

Those things do not have to become evidence that Jesus has left you.

Sometimes they simply reveal where your vision still needs attention.

There is humility in the blind man's answer. Jesus asks him what he sees, and the man does not exaggerate. He does not say, “Everything is perfect now,” because he thinks that is what a person who has been touched by Jesus is supposed to say. He tells the truth. He can see people, but they look like trees.

I think we need more of that kind of honesty in faith.

There are times when the most faithful sentence we can say is, “Jesus, I know You have done something in me, but I still cannot see this clearly.”

There is no shame in bringing Jesus the blurry part.

The dangerous thing is pretending it is clear when it is not.

Peter will soon call Jesus the Messiah, and he will be right. Yet almost immediately he will resist Jesus when Jesus explains the suffering that lies ahead. Peter has enough sight to recognize Christ, but not enough yet to understand the road Christ will walk.

That sounds uncomfortable because we would like spiritual maturity to mean we eventually become people who never misunderstand God.

But perhaps maturity looks different.

Maybe it means we become less defensive when Jesus corrects us.

We stop needing every belief we have held for years to remain untouched. We stop assuming that because we know Scripture, attend church, or have followed Christ for a long time, there is nothing left for Him to clarify.

The middle is not always a failure.

Sometimes it is where Jesus is still teaching us to see.

Chapter 3: When Clearer Sight Changes the Way You Follow

A man leaves a difficult meeting at work and realizes he has spent the whole afternoon thinking about how unfairly he was treated. By the time he reaches home, he has already rehearsed the argument in his head ten different ways. Then, later that evening, something shifts. He starts asking a different question. Instead of only asking, “How do I prove I was right?” he asks, “Jesus, what are You trying to show me about the way I respond when I feel overlooked?” The situation has not changed. His vision of it has.

That is where the healing in Mark 8 reaches into ordinary life. Clearer sight does not always mean receiving more information. Sometimes it means seeing the same situation through a different heart.

The disciples needed that kind of correction. They expected strength to look like control, victory, and visible power. Jesus kept showing them that His way would also include humility, sacrifice, suffering, and trust. Their problem was not that they had no faith. Their problem was that their picture of faith still needed to be sharpened.

The same can be true for us.

We may assume that if God is with us, the path should become easier. We may think answered prayer should always look like immediate relief. We may believe spiritual strength means never feeling afraid, tired, confused, or discouraged. Then life refuses to fit the picture we have carried, and we wonder whether something has gone wrong.

Maybe the picture needs another touch.

Seeing Jesus clearly changes what we expect from Him and what we expect from ourselves. It gives us permission to be honest about what is still blurry without turning that honesty into despair. It teaches us to stop confusing certainty with faith. It reminds us that following Jesus is not about forcing life to fit our expectations. It is about allowing Him to keep shaping the way we see.

The blind man did not heal himself by trying harder to focus. He stayed with Jesus.

That may be the most practical invitation in this entire story. When something feels unclear, stay near Him. Read slowly. Pray honestly. Ask better questions. Be willing to admit when an old assumption no longer fits what Jesus is showing you. Do not rush to call every confusing season a failure.

Sometimes clarity comes in stages.

Sometimes faith grows that way too.

And maybe the surprising part of this miracle is not that Jesus touched the man twice. Maybe the surprising part is how often we need Him to keep touching the way we see.

Your friend,

Douglas Vandergraph

Explore the complete Douglas Vandergraph Master Index:

https://douglasvandergraph.com/douglas-vandergraph-master-index/

Watch Douglas Vandergraph’s faith-based videos on YouTube:

https://www.youtube.com/@douglasvandergraph

The last of him

You already know who he is and how he operates. You know his silence isn't a weapon or a game, but the byproduct of a life lived at maximum capacity. You’ve sat with the awkwardness of the distance, you’ve wrestled with feeling “silly” for caring so much, and yet, underlying all of it, you still carry this deep, genuine affection for him.

​If you stay behind, you'll be left sitting in your room at 10:30 p.m. with the what-ifs. You'll spend the winter wondering if you let fear, or the fear of looking like you cared “too much”, rob you of one last afternoon on the water.

​Going doesn't mean you have to demand answers, fix the silence, or force a storybook ending. It just means showing up as yourself; grounded, open, and willing to take the experience for what it is. It's a chance to step into his world one more time, watch him do what he loves, feel the cold river, and write the final line of this season on your own terms.

​If it’s quiet, let it be quiet. If it’s warm and funny, hold onto that. But give yourself the gift of a proper closing chapter instead of a question mark.

​Go fishing. Be in the magic of it, soak in the wildness, and let yourself say goodbye to this chapter while standing right in the middle of it.

I held a piece of fresh bread near Usain Bolt. Nothing happened. I put that same piece of bread into a toaster, and then turned the toaster on. A few minutes later it popped up, and the bread was toast! That appliance is better at making toast than Usain Bolt. It's not very headline worthy. I keep seeing headlines about other appliances doing things that are being compared to human athletic achievements. Even sometimes stories in the Sports section. Why? What they do has absolutely nothing to do with sport or athleticism. They should be in Popular Mechanics. Like, hey, check this shit out, I wasted the last decade of my life building a thing that looks like a person running! They also need to stop allowing the things to be in human running events. It's just a matter of time before one malfunctions and hurts an athlete or spectator, or gets in the way of an actual athlete breaking a real world record or getting a personal best.

Why is this blog called “The Third Alternative”?

What is this all about, anyway? Well, you've come to the right place for answers. Originally, the title came form a song by the metal band Monster Magnet, but there is nothing beyond that linking the blog to the song or its lyrics. It's just a band I like, and I thought it was a cool song name.

We often see extreme opposites all around us, and many people convinced their way is the best way. It's at the heart of most conflicts. This religion versus that one. This ideology versus that one. This color versus that one. But if you take the time to look deeper, you will notice very few things are black and white. Most thigs in the world are some shade of gray. When two perspectives collide, look for that gray area, look for that third alternative, and you'll be closer to the truth.

Example: you drive to work and someone cuts you off and speeds 30 past the speed limit. You mumble a swear word and shake your head. You call that driver an asshole. You don't think anything past this. We have rules on the road and this driver is clearly a danger to society and, more importantly, a jerk for cutting you off. What if this is a man who just got a call from the hospital and his wife just showed up in ER? Sure, it may not justify putting others on the road at risk, but maybe you will feel less self-righteous judging this “dangerous driver” when you know the full story.

My blog title is a reminder to myself to consider these angles when I write about something divisive.

#opinion

Inbetweeners Part 4- Doors

One of the most unique characteristics of the early Inbetweeners Campaign was how the player characters moved around the world. As described previously, they were brought back to life slightly phased out of reality. As a result, they could not move linearly but instead warped between different locations. The portals through which they warped became known as “doors.” Each “room” had between one and four doors, or portals that would take them to another room. Most portals were two way, one could move back and forth. Others, however, might only move in one direction. Furthermore, some doors were hidden unless players achieved certain conditions, or could only be accessed while certain conditions unlocked.

This novel means of travel did create a few logistical issues in terms of gameplay. First off was the issue of players abusing the mechanic, being halfway through one door and another. This also created logistical issues for the DM— how does it work if atmospheric and other conditions vary vastly among the two locations? When players go through, can other NPCs see the alternate location? To resolve this, I decided the doors are only visible to the players and traveling through them was a binary. You were either in one room or another. So take for example The Market. This was a large, bustling market in a major town square. Two of the gates into and out of the market served as portals, as well as an abandon stall and a refuse trough. The gates were simple, if a character walked through one they'd suddenly be somewhere else, vanishing to anyone watching, whereas any NPC would just walk through the gate as normal. The abandon stall was a shopping stall with no vendor, if a player tried to go behind the table or into the stall they would suddenly find themselves in the dining room of an abandon haunted mansion, next to a table covered in cobwebs with skeletons sitting in each seat. The refuse trough was a disgusting trough of excrement, vomit, stagnant water and rotting food. If the players came close enough to touch it, they would suddenly disappear from the market and appear inside of a massive oven that immediately activates.

The “infernal oven” was interesting because the door out of it back to the market wasn't immediately accessible. Instead, they had to find a way to break through part of the oven to find a release hatch. So sometimes characters would not spawn directly next to the door they want through. This created another issue though- difficulty scaling. Some of the rooms were very challenging, and the players were only level 1. I needed a way for them to not be terrified to travel through new doors. If certain death could wait on the other side, it really disincentivizes exploration. Since the players were not the Interloper's first participants, he had encountered this issue before. Many participants would leave to explore the rooms and simply never return. My thought is that for each new batch of participants, they had a completely separate batch of doors and rooms, linked to the time and way in which they were brought back. Almost like RNG on a map generator. So, the Interloper needed to find a way to reduce attrition of his participants or he would never gather sufficient samples and research material. Since he exists slightly outside of space-time, he can use this to his advantage in limited ways. Basically, when players go through a door, there is a strong emotional anchor to how they react to what is on the other side. That small piece of information can be sent back in time enough to code a door. So the Interloper created a simple heuristic- green means relatively safe and red means relatively dangerous. The more red the door, the more dangerous whatever is behind it. So the most blindly bright red door was the one that led to Zariel's War Room. This makes sense because collectively all the devils behind it probably amounted to a CR 30 encounter. However, that doesn't mean the entities will immediately attack. Zariel's devils were more interested in interrogation to figure out how the characters penetrated the fortress. But, very dangerous, hence red. On the flip side, the market is green, since it is just a bustling market with various vendors. Basic town guards are present, but they only present a threat to minor criminals so no real threat there. A third category, purple, was used to indicate that a room was “interesting”. This means that it is unusual in some way, or has some feature that other doors/rooms do not. It says nothing about the threat level behind the door. The door that leads to a temple based on which religious relic or icon you present was purple. This makes sense because a temple of Chauntea would be completely safe, vs a temple of Bane might be very dangerous.

The doors did present some novel challenges. Since players couldn't leave a room except through a door, if they were captured, their captors would attempt to take them outside the area only for the players to appear on the other side. This made for some comical instances where the captors would repeatedly move them back only to realize they had to build a makeshift prison in place.

Later in the campaign, when players wanted to go to a specific location outside the rooms, the Interloper was able to create temporary doors, though sometimes they brought the players to a place slightly different than intended. There was also a branch of doors with no hue or warning. These were not created by the Interloper but rather by the Lady of Pain as she initially tests the Inbetweeners, though they were unaware of this at the time. Those doors held grave dangers but no warning.

Once the players had to flee the Grey Room after the Protectors of the Weave invaded and head to the Sigil for safety, they were then bound to Sigil for part of the campaign. In Sigil they moved about normally, since it is a four dimensional city run by the Lady of Pain, who herself was originally from outside the multiverse and as a result, operates on a different planar geometry. It was not until the players completed the Xalatra Questline (which there will be a later post about, at some point) that they were able to travel normally. This did involve covering their bodies with protective runes and then jumping through “The Maw”, which broken them down at a subatomic level and recreated them in such a way that the flaw in the Interloper's resurrection was fixed. At this point, the “door” mechanic in the campaign ended entirely. One could say the doors were a mechanic for the multiplanar dungeon crawl stage of the game, but no longer served a purpose when it broadened out into an epic fantasy.

Inspired by the 5 Albums post, I was thinking about the 5 fiction books that shaped me. I am going mostly from memory. I just want to list whatever comes to my mind first. These are all books that influenced my reading life in one way or another.

1. The Hobbit / Lord of the Rings Trilogy by J.R.R. Tolkien: Yeah, I know, not one book. I am already bending the rules here. But I cannot talk about LOTR without The Hobbit, and vice versa. I would also include The Silmarillion here as well. I was completely immersed in this fantasy world from the first time I read The Hobbit.

2. Dune by Frank Herbert: It has been a while since I read this one, but I remember it blew my mind back then. I am secretly afraid of re-reading this book and getting disappointed (I am not sure it aged well). But from what I remember, the complex politics and alien world elements got me super interested in this type of sci-fi.

3. I, Robot by Isaac Asimov: This is another one that I consider a whole series, but this was the first book I read. I loved learning about the positronic brain and the laws of robotics. It was fascinating to see a robopsychologist! I will also include The Caves of Steel and The Naked Sun here. Great sci-fi! I want to read them all again.

4. Sherlock Holmes by Arthur Conan Doyle: I absolutely love these books! I can read them over and over. They are great! I used to have a collection of used Sherlock Holmes books. The first time I read them, I borrowed them from the library. After that, I would go to used bookstores and try to find old editions. I love the way Sherlock Holmes pays attention to the smallest details and comes up with deductions using logical reasoning. When the mystery is solved, it is so satisfying!

5. The Hitchhiker's Guide to the Galaxy by Douglas Adams: Again, the whole series is included here. These books are a masterpiece of clever humor with scientific nuggets of information. I love how it makes fun of technology, plays with the laws of physics, and is just so much fun. I recently listened to the first two audiobooks, and they are so good!

And now that listed them all I realized it's a list of 5 book series! Ok, I’ll change the title. So, there you go!

— Post 12 of #Blaugust #Books

Yesterday, we had nothing. nothing to say nor complain about. but today? Oh, today we have a complaint. ladies and gentlemen, we are officially back with my basic complaints, so get comfortable. get your blankets, lock the closet, check under the bed. because we’re doing horror today, or, well, what they’ve decided to call “horror”. though, i think i missed the horror somewhere. i went to watch ‘Insidious: Out of the Further’ today, and before anyone gets offended, yes. i found it boring. i think i have finally figured out my problems with horror movies, i dont actually like them. shocking? i know. its just that whenever a movie proudly labels itself “horror” i expect at least some sense of horror, fear. tension. something that makes me sit there and think, maybe i shouldn’t turn the light off tonight. Hasn’t happend once. not a single horror movie ive watched has actually frightened me. not even enough to give me that stupid feeling of checking the corner of my room afterwards. they’re just boring. something jumps out, someone screams too loudly, and the music gets awfully loud, and thats supposed to be terrifying? im supposed to be terrifed? No, i know its acting im not as dumb as you, i know the ghosts arent real and nobody is actually being dragged yadda yadda. the part that i hate the most. nothing feels honest, everything feels staged in the most obvious way possible. the characters behave like any other “horror” movie is expected to behave, act idiotic, scream at nothing and decide to investigate noises alone because common sense was left outside. and Insidious does plenty of that. plently of nonsense, basic horror movie act, oh a dark creepy house, oh strange things happening. How scary, seriously? you call that horror? someone needs to speak to the movie directors i think they accidentally made a childrens bedtime story and forgot to add the bedtime. i almost fell asleep. give me something that feels possible. something that doesnt announce itself with dramatic music and conveniently timed shadow. otherwise, congratulations. you made me stare at a screen with popcorn loud chewers for two hours and feel absolutely nothing but annoyed. boring to dust.

Anyway, that was my complaint for today. tomorrow i’ll find something else to complain about. im sure the world will provide me something as dumb as staying in a notoriously haunted house and treating a literal face scraping demon like an obnoxious roommate who refuses to pay rent.

Sincerely, Dont watch horror movies, kids. you might mistake it for bedtime stories.

Finished only this morning, another title by Jenny Erpenbeck, The Book of Words, a 150-page novella detailing a woman’s recollections of childhood, which take on a progressively more menacing and unnerving cast as they go on. Compared to Go Went Gone, it’s perhaps more stylistically refined — beautifully well-written — though meanwhile a little less to my taste than the later novel. The translation, again by Susan Bernofsky, seems excellent.

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On Saturday I read The Other Girl by Annie Ernaux, translated from the French by Alison L. Strayer. This is a very slim volume, with the body of the text not amounting to fifty pages, so it didn’t take long to traverse it. At the bookshop in Chepstow that morning I’d first picked up a different Fitzcarraldo title, and had then wondered if there were any of their several volumes of Ernaux’s memoirs & essays on the shelves: as it happened, there was only this one. The book is in the form of a letter by Ernaux to the sister she never met. Ginette Duchesne had died aged 6, in 1938, of diphtheria. Annie was born two years later. As she recalls it, her parents never directly talked to her about her sister, and she describes overhearing her mother talk about ‘the other girl’ only once. Nor did Ernaux ever question her parents about Ginette, whose unspoken absence nevertheless continued to haunt them all:

...you and I were fated to be only children. Their desire to have just one child, which they made very clear (we couldn’t do for two what we are doing for one), meant it was either you or me, but not both... It took almost thirty years [...] for it to hit me: I was born because you died, and I replaced you.

It’s a powerful little book. At times reading it felt uncomfortably like intruding on a series of private moments. On the strength it I’m now keen to read Ernaux’s The Years, though I don’t know if I’ll want to venture much further into her bibliography than that.

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No new music arrived this week. Instead I can mention a couple of recent acquisitions overlooked in previous posts: Grasshopper (1982) by J.J. Cale, and Quiet (1996) by John Scofield. After Naturally, Troubadour and Travel-Log, Grasshopper is my fourth J.J. Cale album on vinyl. I don’t think it’s unfair to say it’s neither one of the best nor the worst of his records: even so, mid-tier J.J. is well worth my time & attention. ‘City Girls’ was the lead single from it, and perhaps its most memorable tune.

Reading on-line about John Scofield’s album A Go Go, which I bought last month, I saw it had followed a very different release, Quiet, on which the guitarist had played only acoustically, accompanied by drums, bass, and a seven piece horn section, augmented on a couple of numbers by Wayne Shorter on the tenor sax. I obtained a reasonably inexpensive second-hand CD copy via ebay. It’s a subtle and low-key collection of good tunes in elaborate arrangements, all beautifully played. It may not be among Scofield’s best-regarded albums, but it hits a sweet spot for me. Opener ‘After the Fact’ establishes the mood very nicely.

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After finishing a bottle of Ardbeg last month, I opened something very different on Wednesday evening in the shape of ‘The Targe 30 year-old Highland Single Grain scotch whisky’. When I bought it at Lidl the year before last it was originally earmarked as a gift for someone else. Plans changed, and I kept it instead in reserve for myself. Its time to shine has now finally arrived. My one prior experience of a single grain whisky (sampled decades ago), hadn’t thrilled me, but, on the grounds that it’s all too seldom I can afford to try anything that has languished in a cask for thirty years, I’d been curious to try this one anyway. It’s a light & clean sort of dram, with initial impressions of mellow sweetness in which I discerned notes of coconut crumb and vanilla. Unsurprisingly there is woodiness too, with a typical whisky sourness eventually also asserting itself. It’s very smooth and affable with no murky depths: an interesting change of scenery I think I’ll enjoy.

Agosto | Preguntas sin respuesta

¿Quién me está lastimando?

Me siento triste.

Tengo una batalla interna entre lo que quiero y lo que no quiero. Tengo los ojos llenos de lágrimas. Tenía mucho tiempo que no lloraba, y mucho menos por situaciones así.

Por eso no me gusta sentir.

Siento que cuando lo hago, saco lo peor de mí.

Pero ¿Qué es la vida sin un poco de dolor?

Y entonces aparece la pregunta que no sé contestar:

¿Qué es realmente lo que me lastima?

¿Mi cabeza? ¿La realidad? ¿Quién me lastima? ¿O me lastimo yo misma?

¿Por qué idealizo a la gente? ¿Por qué me cuesta tanto hacer preguntas? ¿Por qué no me doy mi lugar?

¿Por qué, por qué, por qué...?

Por eso me alejo.

Por eso prefiero no sentir nada. Por eso me cierro.

Porque sé que cuando siento, siento demasiado.

No puedo controlar mis emociones. Mis ojos no dejan de llorar y ya no quiero sentirme así.

A veces incluso creo que me lo merezco.

Pero, realmente, ¿Qué mal he hecho yo para merecerlo?

No creo que ninguno.

¿O exagero la realidad?

¿Cómo puedo vivir en la realidad cuando tengo que lidiar con mis miedos y mis deseos?

¿Y qué deseo?

Libertad. Independencia. Amor. Conocer el mundo. Viajar.

Básicamente creo que todo eso es lo mismo.

Pero entonces, ¿Qué tiene de único? ¿Qué tiene de diferente?

Tengo miedo de morir sin amar de verdad.

Tengo miedo de no hacer lo que quiero porque mi cabeza no me lo permita.

Tengo miedo de no vivir.

De no vivir mientras pueda.

Porque si algo sé es que la vida no es eterna.

Entonces, ¿por qué desperdiciar el tiempo?

¿Por qué dar las cosas por sentadas?

¿Por qué conformarse?

Me da miedo ser conformista.

Me da miedo sentir tanto.

Porque cuando uno siente mucho por las personas, también les da el poder de lastimarnos.

Así me pasó.

Con mi mejor amiga.

Ella también me duele.

A veces no entiendo por qué la perdí.

Y tengo miedo.

Tengo miedo de no ser amable conmigo.

De reprocharme tanto.

De sentir que merezco sufrir.

De pensar que las personas son superiores a mí.

¿Por qué no soy amable conmigo?

¿Por qué no pienso de mí lo mismo que pienso de los demás?

Siempre trato de ver lo mejor de todos.

¿Por qué no puedo hacer lo mismo conmigo misma?

¿Por qué siempre veo mis defectos?

Es como verme en un espejo y estar buscando constantemente un error.

Pero ¿por qué?

Quizá esa sea la pregunta que queda cuando todas las demás se han agotado.

No sé quién me está lastimando.

No sé si es la realidad, mi cabeza, las personas que quiero o la forma en que he aprendido a quererlas.

Pero esta noche, por primera vez en mucho tiempo, estoy llorando.

Y quizá no tenga que encontrar una respuesta todavía.

Quizá por ahora solo necesito dejar de preguntarme qué está mal conmigo.

Quizá necesito aprender a mirarme sin buscar un error.

A Quick Win.

I won this club-based CC (Correspondence Chess) game this morning with a Queen-Rook combination Checkmate on my 25th move. We started play on 08 August, so that means only 17 days transpired from the game's opening move until its conclusion. For me, that's a very quick game. I prefer playing with at least 3 days allowed per move. I have some games now in progress where my opponents and I are allowed 14 days per move.

Anyway, the position of pieces at game's end is shown above, and our full move record follows: 1. d4 d5 2. Nc3 Nf6 3. Nf3 Nc6 4. e3 Bf5 5. Bb5 Qd7 6. Ne5 Nxe5 7. Bxd7+ Nexd7 8. O-O e6 9. Re1 O-O-O 10. a4 Kb8 11. b4 Bxb4 12. Bb2 e5 13. a5 Bxc3 14. Bxc3 exd4 15. Bxd4 Rhg8 16. Rb1 c5 17. Bc3 Ne4 18. Bb2 g6 19. Qxd5 Ndf6 20. Be5+ Kc8 21. Qxb7# 1-0

And the adventure continues.

This short essay published on The Marshall Review, marks the beginning of a larger project: defining the discipline of publication architecture. It doesn’t explain the method – that comes later – but it sets out the central idea that a publication is an intellectual structure, not a stream of content. The role of the Publication Architect is to design that structure so meaning can accumulate over time.

https://rvw.ie/h1the-publication-architect-brwhy-structure-matters-more-than-content-h1