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Photography Reviews Writing

An Amateur Photographer’s Mid-Term Review of the Leica Q2

Black-and-white street crowd at Yonge–Dundas; older woman adjusting hood, masked pedestrians, large bank ad billboard behind.”
(Yonge & Dundas, Toronto, 2024)

I’m an amateur Toronto-based documentary and street photographer, and have been making images on the street for over a decade. In the fall of 2023 I purchased a used Leica Q2. I’d wanted the camera for a while, but it wasn’t until late 2023 that I began running into situations where I’d benefit from a full-frame sensor. Since then I’ve been going out and making images with it at least once a week for hours at a time and have made tens of thousands of frames in all kinds of weather.

In this post I discuss my experiences using the Leica Q2 in a variety of weather conditions to make monochromatic JPG images. I tend to exclusively use either single-point autofocus or zone focusing, and either multi-field or highlight-weighted exposure modes, generally while using aperture priority at 1/500s to freeze action on the street. My edits to images have, previously, used Apple Photos and now rely on the Darkroom app on my iPad Pro. You can see the kinds of images that I’ve been making on my Glass profile.

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Writing

Dromology in the Age of Synthetic Cognition

Paul Virilio was a French cultural theorist well known for his theory of dromology. Dromology explores the logics and impacts of speed in the modern era. At its core, it theorizes how the velocity of action or decision-making enables actors to accrue wealth and power over others. Virilio often approached this concept through the lens of martial power, contemplating how new means of movement — the horse, the automobile, telemetric control — created new capacities to overcome the frictions of time and space, and to overcome adversaries through heightened sensing and accelerated decision-making.

We exist in an era of digital intensification. Cybernetic systems are now core to many people’s daily realities, including systems over which they have little meaningful influence or control.1 Earlier digital modernity was often described as an “attention economy.” Today, we may be entering what I’ll call a “velocity economy,” which is increasingly grappling with the implications of a faster-moving world.

Escape Velocities

Om Malik has written recently on velocity and how it may now precede attention as a structuring condition:

What matters now is how fast something moves through the network: how quickly it is clicked, shared, quoted, replied to, remixed, and replaced. In a system tuned for speed, authority is ornamental. The network rewards motion first and judgment later, if ever. Perhaps that’s why you feel you can’t discern between truths, half-truths, and lies.

Algorithms on YouTube, Facebook, TikTok, Instagram, and Twitter do not optimize for truth or depth. They optimize for motion. A piece that moves fast is considered “good.” A piece that hesitates disappears. There are almost no second chances online because the stream does not look back. People are not failing the platforms. People are behaving exactly as the platforms reward. We might think we are better, but we have the same rat-reward brain.

When velocity becomes the scarcest resource, everything orients around it. This is why it’s wrong to think of “the algorithm” as some quirky technical layer that can be toggled on and off or worked around. The algorithm is the culture. It decides what gets amplified, who gets to make a living, and what counts as “success.”

Once velocity is the prize, quality becomes risky. Thoughtfulness takes time. Reporting takes time. Living with a product or an idea takes time. Yet the window for relevance keeps shrinking, and the penalty for lateness is erasure. We get a culture optimized for first takes, not best takes. The network doesn’t ask if something is correct or durable, only if it moves. If it moves, the system will find a way to monetize it.2

The creation and publication of content — and the efforts to manipulate engagement metrics to juice algorithms — have long been partially automated. Bot and content farms are not new. What may be new is the scale and ease of synthesis. As the cost of producing text, images, summaries, and responses to each declines through the widespread adoption of LLMs and agentic systems, the volume of generated material increases dramatically.

That increase in volume does not just mean “more noise.” It alters competitive dynamics and means that velocity — which then accrues attention — becomes key in an algorithmically intermediated world. In this environment what is increasingly put under pressure are decisional latencies — the time between sensing, synthesizing, and acting. And humans are making decisions on what to focus on based on automations and algorithms designed to cull out what they “should” be paying attention to.

Earlier digital acceleration primarily affected distribution: messages moved faster, and telemetrics enabled the expression of power at heightened distances, as examples. Now we may be witnessing the acceleration of what looks like cognition. LLMs have no theory of mind insofar as they do not “understand” in any human sense. Yet they can synthesize, summarize, categorize, and prioritize at speeds that mimic cognitive activity. And when those synthesized outputs are connected to agentic systems capable of taking action — filing forms, executing transactions, triggering workflows — we move beyond accelerated messaging into accelerated execution. Decisional latencies can become compressed in order to produce outputs that move sufficiently fast, and with sufficient purchase, to be registered by algorithms as worthy of amplification and, ultimately, human attention.

Put differently: as velocity becomes a mode of capturing attention there is pressure to move more quickly in the face of other, similarly fast-moving outputs, and in ways that potentially exploit or game algorithms in an effort to obtain human attention.

New Velocity, New Harms

For Virilio, every accelerant technology carried with it a corresponding accident. The invention of the ship implied the shipwreck. The car led to the car crash. Radio and telecommunications enabled new forms of propaganda and coordinated deception. And so on.

LLMs and agentic systems may carry their own accident structures. They enable mass automated persuasion at scale. A flaw in a widely deployed foundation model could result in class-breaking errors replicated across applications dependent on that model.3

Agentic systems introduce further risks: cascading autonomous mis-executions, rapid propagation of flawed decisions, and compounding feedback loops that create significant problems before humans detect them.4

AI accidents have the potential to be more distributed and more simultaneous than prior automation failures. While automated systems have long-posed risks the generalized and cross-sector nature of foundation models could expand the blast radius of automated harms. When many systems rely on shared models or shared training data, correlated failures become more plausible.

Velocity, in this sense, does not merely amplify error; it compresses the window in which errors can be identified and corrected. It risks creating brittle systems and generating what Charles Perrow has called “normal accidents.”

Velocity and Organizational Impacts

If decisional latency becomes the friction to be minimized in a velocity economy, organizations may feel pressure to shorten analytic cycles and accelerate workflow tempos. In domains where speed confers agenda-setting power, organizations may need to move faster or risk marginalization.

At the same time, we might see a divide emerge. Some institutions may further prioritize velocity and first-mover visibility as a way to shape agendas. Others may deliberately preserve slower processes to protect legitimacy and safety. Friction — often treated as inefficiency — may be read as functioning as a source of institutional credibility.5 It may, also, be used by some organizations to justify their resistance to innovation and with the effect of falling behind other actors.

As information volume expands, organizations and individuals may increasingly depend on third-party systems to track, assess, and prioritize what is “meaningful.” LLMs and agentic systems may be paired with other automated triage systems designed to impose order on informational abundance.

Yet such sense-making is inherently lossy. The world is dense with detail, contingency, contradiction, and edge cases. When LLMs normalize information statistically, much of that raw specificity can be abstracted away. The effect can be that important context is never surfaced for human review; reliance on abstracted assessment systems to navigate a digitally intermediated world may entail a further loss of representational fidelity.

This abstraction is not unprecedented — humans have always distilled complexity — but the scale and automation of the distillation may be new. And as (or if) human review recedes the capacity to interrogate what has been smoothed over may diminish.

Organizations must also determine when they will introduce human review as well as when they will deliberately refrain from doing so. Prioritizing human assessment of all outputs could introduce friction that other organizations or jurisdictions may not demand. A majority-human-review organization may operate outside the dominant tempo of a velocity economy, with the end of potentially gaining legitimacy and safety while simultaneously sacrificing influence or timeliness.

Organizational Consequences of LLM and Agentic Velocity

If LLM- and agentic-enabled systems increase the rate at which information is generated and decisions are executed, several consequences may follow.

  1. The distribution of power may become linked to access to compute, to foundational models, to reliable data, and to the capacity to act digitally or physically. Countries that dominate the production — or regulation — of foundational models may accrue disproportionate influence. Where production and regulation of AI models or systems diverge between nation-states or geopolitical regions, conflicts over norms and authority may intensify.
  2. Organizations may need fast initial outputs to secure attention in a velocity-based information environment. However, rapid outputs need not be final outputs. Deeper analysis may continue in parallel, informing subsequent action and ensuring that longer-term activities based on such analysis remain well grounded in facts and aligned with strategic priorities. Organizations that excel at this two-track approach to knowledge production may gain strategic benefits in being able to set agendas as well as subsequently navigate them with complexity, depth, and institutional integrity.
  3. Where agentic systems are entrusted to make certain classes of judgments, institutions must determine under what conditions (and to what extent) they will add the friction of human oversight. The more friction introduced, the greater the potential divergence from competitors operating at full automation speed. At the same time, human-informed decision-making may confer benefits of perceived legitimacy and safety.
  4. Institutions must carefully consider how they can, and cannot, adopt LLMs and agentic systems so they are responsive to changes in the lived reality of the world while at the same time working to carefully protect social trust that they possess. There may be increased pressures on institutions to align their decisional horizons with machine-accelerated and innovation-driven time horizons, perhaps requiring shifts in decisions from slow and fixed in time, to more fast moving and subject to routine revisions. For bureaucratic organizations or institutions this could require major changes6 in decisional structures and processes.

Future Looking Velocity-Imposed Pressures

If we are to take Virilio’s insights seriously, along with changes in technological activity per Malik’s thoughts, then there are at least three tensions worth watching:

  1. Organizations with access to contemporary models may be able to move more quickly and accurately, with the effect of reducing the time delta in summarizing or producing information while compressing decisional cycles. At risk, however, is whether this elides the specificity that is reflective of the actual world and has the effect of delegitimizing actual decisions as a result of minimal (or insufficient) human oversight or governance. To what extent might LLM- and agentic-forward organizations make bad decisions more quickly and undermine their legitimacy? How much will access to contemporary models differentiate between organizations’ abilities to undertake rapid-pace sense-making and decision making?
  2. Epistemic pressures may worsen as synthetic media is produced at scale and automated intermediaries filter what humans encounter. What happens when your digital assistant, or one your organization relies on, has been sorting content for months, only for you to discover it has been amplifying propaganda because of model poisoning or bias you did not anticipate? What to do when the decisions you’ve been making have unknowingly been badly torqued to the advantage of other parties?
  3. Class-breaks that result in cascading failures become more plausible in monocultural model ecosystems. To what extent does widespread reliance on common foundation models create systemic points of failure that are difficult to detect, diagnose, or correct? Will this encourage the development of more ‘small models’ in an effort to stem or mitigate these kinds of security impacts?

Virilio suggested that speed restructures power. Malik suggests that velocity now structures visibility and attention. If LLMs and agentic systems compress not only communication but also enable synthetic cognition and decisional executions, then the next few years may test whether institutions can preserve legitimacy, trust, and factually-driven actions and decisions in a world increasingly oriented around motion.

It will be interesting to assess whether friction comes to be seen increasingly as an obstacle to wealth or power, or whether organizations that maintain appropriate degrees of friction preserve (or expand) their legitimacy relative to those that move quickly and break things.


  1. Examples include automated bots interacting with global capital markets, and the automated balancing of critical infrastructure systems to enable seamless continued services. ↩︎
  2. Emphasis not in original. ↩︎
  3. In computer security, a “class-break” refers to a vulnerability in a widely used underlying technology such that an exploit affecting one instantiation effectively compromises the entire class of systems built upon it. For example, a flaw in a common cryptographic library can render all software relying on that library vulnerable simultaneously. ↩︎
  4. If humans even ever do detect them… ↩︎
  5. While not taken up, here, this divide between moving quickly versus slowly may have interesting implications for agenda-setting windows, and the development and proposals of policy problems and solutions. ↩︎
  6. Perhaps even existential changes! ↩︎
Categories
Links Writing

Trusted Content Calls for Trusted Identities

Adam Mosseri recently posted about how Instagram is evolving to arbitrate what is, or is not, truthful in a generative AI era. Om Malik’s analysis of said post is well worth the time to read and, in particular, his framing of Instagram’s movement into what he calls a ‘trust graph’ era:

[Instagram] has moved from the social graph era, when you saw posts from people you knew, to the interest graph era, when you saw what algorithms though [sic] you will like. It is now entering a trust graph era, in which platforms arbitrate authenticity. And it is being dragged into this new era. [^ Emphasis added.]

AI is flooding the system, and feeds are filling with fakes. Visual cues are no longer reliable. Platforms will verify identities, trace media provenance, and rank by credibility and originality, not just engagement.

Malik’s framing is useful not simply because it captures a product evolution, but because it gestures toward a deeper shift, and one whose implications extend well beyond Instagram as a platform. Namely, platforms are positioning themselves as arbiters of authenticity and credibility in an environment where traditional signals of truth are increasingly unstable.

There are some efforts to try and assert that certain content has not been made using generative systems. Notwithstanding the visibility that Meta possesses to try to address problems at scale, what is becoming more salient is not merely a technical response to synthetic media, but a broader epistemic and ontological shift that increasingly resembles Jean Baudrillard’s account account of simulacra and life lived in a state of simulation:

Simulacra are copies that depict things that either had no original, or that no longer have an original. Simulation is the imitation of the operation of a real-world process or system over time.

This framing matters because efforts to ground authenticity and truth are predicated on the existence of an original, authentic referent that can be recovered, verified, or attested to.

Generative AI content can, arguably, be said to largely be divorced from the ‘original’ following the vectorization and statistical weighting of content; at most, the ‘original’ may persist only as a normalized residue within a lossy generative process derived from the world. Critically, generative systems do not simply remix content; they dissolve the very reference points on which provenance and authenticity regimes depend. And as generative LLMs (and Large World Models) are increasingly taken up, and used to operate the world in semi-autonomous ways, rather than to simply represent it, will they not constitute an imitation of the operation of real-world processes or systems themselves?

This level of heightened abstraction will, to some extent, be resisted. People will seek out more conservative, more grounded, and perceptibly more ‘truthful’ representations of the world. Some companies, in turn, may conclude that it is in their financial interest to meet this market need by establishing what is, and is not, a ‘truthful’ constitutive aspect of reality for their users.

How will companies, at least initially, try to exhibit the real? To some extent, they will almost certainly turn to identity monitoring and verification. In practice, this means shifting trust away from content itself and toward the identities, credentials, and attestations attached to published content. In this turn, they will likely be joined by some jurisdictions’ politicians and regulators; already, we see calls for identity and age verification regimes as tools to ameliorate online harms. In effect, epistemic uncertainty about content may be displaced onto confidence in identities attached to content.

This convergence between platform governance and regulatory activity may produce efforts to stabilize conservative notions of truth in response to emergent media creation and manipulation capabilities. Yet such stabilization may demand heightened digital surveillance systems to govern and police identity, age, and the generation and propagation of content. The mechanics of trust, in other words, risk becoming the mechanics of oversight and inviting heightened intrusions into private life along with continued erosion of privacy in digital settings.

Regardless of whether there is a popping of the AI bubble, the generative AI systems that are further throwing considerations of truth into relief are here to stay. What remains unsettled is not whether platforms will respond, but how different jurisdictions, companies, and regulators will choose to define authenticity, credibility, and trust in a world increasingly composed of simulacra and simulations. Whether the so-called trust-graph era ultimately serves users—or primarily reasserts institutional authority under conditions of ontological and epistemic uncertainty—will remain one of the more intriguing technology policy issues as we move into 2026 and beyond.

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Aside

2025.12.30

Managed to walk into — and out of — a Leica store and only bought a pin. I really wanted to get the used Q2 Monochrome that was ‘only’ 4750 euros.

Though I did buy the Leica Academy inspiration book, online and used, after leaving. But I refuse to count it because it’s a published-based purchase!

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Links

Vibe-Coded Malware Isn’t a Game Changer (Yet)

Over the past week there’s been heightened concern about how LLMs can be used to facilitate cyber operations. Much of that concern is tightly linked to recentreports from Anthropic, which are facing growing criticism from the security community.

Anthropic claimed that a threat actor launched an AI-assisted operation which was up to 90% autonomous. But the LLM largely relied on pre-existing open source tools that operators already chain together, and the success rates appear low. Moreover, hallucinations meant that adversaries were often told that the LLM had done something, or had access to credentials, when it did not.

We should anticipate that LLMs will enable some adversaries to chain together code that could exploit vulnerabilities. But vibe‑coding an exploit chain is not the same as building something that can reliably compromise real systems. To date, experiments with vibe‑coded malware and autonomous agents suggest that generated outputs typically require skilled operators to debug, adapt, and operationalise them. Even then, the outputs of LLM‑assisted malware often fail outright when confronted with real‑world constraints and defences.

That’s partly because exploit development is a different skill set and capability than building “functional‑enough” software. Vibe coding for productivity apps might tolerate flaky edge cases and messy internals. Exploit chains, by contrast, often fail to exploit vulnerabilities unless they are properly tailored to a given target.

An AI system that can assemble a roughly working application from a series of prompts does not automatically inherit the ability to produce highly reliable, end‑to‑end exploit chains. Some capability will transfer, but we should be wary of assuming a neat, 100% carry‑over from vibe‑coded software to effective vibe‑coded malware.

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Links

Even Minimal Data Poisoning Can Undermine AI Model Integrity

As reported by Benj Edwards at Ars Technica, researchers demonstrated that even minimal data poisoning can implant backdoors in large language models.

For the largest model tested (13 billion parameters trained on 260 billion tokens), just 250 malicious documents representing 0.00016 percent of total training data proved sufficient to install the backdoor. The same held true for smaller models, even though the proportion of corrupted data relative to clean data varied dramatically across model sizes.

The findings apply to straightforward attacks like generating gibberish or switching languages. Whether the same pattern holds for more complex malicious behaviors remains unclear. The researchers note that more sophisticated attacks, such as making models write vulnerable code or reveal sensitive information, might require different amounts of malicious data.

The same pattern appeared in smaller models as well:

Despite larger models processing over 20 times more total training data, all models learned the same backdoor behavior after encountering roughly the same small number of malicious examples.

The authors note important limitations: the tested models were all relatively small, the results depend on tainted data being present in the training set, and real-world mitigations like guardrails or corrective fine-tuning may blunt such effects.

Even so, the findings point to the ongoing immaturity of LLM cybersecurity practices and the difficulty of assuring trustworthiness in systems trained at scale. Safely deploying AI in high-risk contexts will require not just policy oversight, but rigorous testing, data provenance controls, and continuous monitoring of model behaviour.

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Photography

Automate Screen Brightness for Photography Apps

Several years ago I posted about a “Glass Time” shortcut. When activated it opened the social media application I use to post and view photography — Glass — and then increased the brightness to 100%. The intent was to ensure I was looking at images closer to how the photographer intended.

The only issue was that I needed to remember to activate the shortcut instead of opening the application itself. This worked but was a bit clunky, and so I’ve created a more pleasant way to achieve the same thing.

Enter some Apple Shortcuts and Automations.

Mission Statement

I wanted my screen brightness to jump to 100% whenever I opened Glass or my photo editor (Darkroom) and then drop back down to 50% once I closed them.

Components

To make this work I had to create Apple Shortcuts and Automations. The shortcuts handle the brightness setting and the automations tell your device when to run those shortcuts. Specifically, I needed an:

  • Apple Shortcut that, when activated, increased the screen brightness to 100%
  • Apple Shortcut that, when activated, reduced the screen brightness to 50%
  • Apple Automation that triggered 100% brightness when opening Glass, and a separate Apple Automation that did the same thing when opening Darkroom.
  • Apple Automation that triggered 50% brightness when closing Glass, and a separate Apple Automation that did the same thing when closing Darkroom.

Building and Linking Components

The process for creating the various components was very easy. To create the underlying Apple Shortcuts:

  1. Open Apple Shortcuts
  2. Tap/click the “ ” button, and in the search bar search for “Set Brightness”
  3. Set the Brightness slider to 100%. Modify the name of the shortcut to something like “Set Brightness 100%”.
  4. Create a second shortcut the same way, but set the slider at 50%. Name the shortcut something like “Set Brightness 50%.”

To create the automations to trigger the different screen brightness levels:

  1. Open the main screen of Apple Shortcuts.
  2. Tap/click “Automation” on the menu bar.
  3. Tap/click the “ ” button to create a new automation. Select “App” in the menu, choose either Glass or Darkroom (or another application of your preference), and the radio button “Is Opened.” Have the automation run immediately. Tap/click “Next”.
  4. In the next screen, scroll to find your Apple Shortcuts “Set Brightness 100%” in “My Shortcuts.” Your automation is now completed and the brightness will go to 100% when opening the relevant application.
  5. Repeat steps 1-4, but modify the radio button chosen in step 3 to “Is Closed”, and in step 4 choose the “Set Brightness 50%” shortcut.

Limitations of Automations

Your Apple Shortcuts will sync between all of your Apple devices through iCloud but this will not occur with your Apple Automations. This means that you’ll need to repeat the automation steps on all of your devices that you want the automation to activate on.

Categories
Photography Writing

The Beauty of the Everyday

I really liked Robin Wong’s reflection on why he keeps returning to the same streets to make his images.

the beauty of doing the same routines, walking the same paths is the familiarity of the location, and you know every turn and corner, you know the details inside out, so you can be prepared for the unexpected. That is also the exciting part of shooting on the streets, you will find something unusual, something you will not know will happen beforehand, and the surprise is worth the redundant process of walking the same streets all over again. […] It isn’t about finding something completely new or extra-ordinary to shoot but finding beauty in the most ordinary settings and make it worth clicking your shutter button for.[^ Emphasis added.]

Like Wong, I’ve found that familiarity can sharpen my eye. Because I walk the same places regularly, I’m able to find the images I do. Having seen the same scene hundreds of times, I can tell when something has changed or that there’s some novelty in the scene that’s before me.

To some extent I think of regularly seeing the same scenes a little like drinking whiskey. At first, whiskey just tastes hot and spicy; any differences seem more theoretical than real. But over time you notice subtle nuances and also detect rarified variances between what you’re enjoying. And you can get excited over little things that really aren’t apparent or distinguishable to someone that hasn’t built up the same kind of palate.

When you walk the same streets over and over, you develop your own sense of what should and shouldn’t be there. You can detect what’s normal or novel. By training your eye on these common spaces, you develop your style. If you need to find something novel in the same place over and over, you’ll develop a unique way of seeing the world, whereas if you’re always seeing a new place you don’t need to stretch in quite the same way — you don’t need to push yourself to develop your sense of what is visually interesting to you.

All of which is to say: from afar, street photography can look pretty dull or boring because there’s a lot of repetition. It’s exactly this repetition, however, that helps you discover the kind of photographer you are.

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Solved

Solved: Apple Wallet Card Activation on a New iPhone

When I set up my new iPhone 17 Pro I ran into a frustrating problem: I couldn’t activate some of my credit and banking cards in Apple Wallet. Since this might happen to others, here’s how I diagnosed the issue and worked around it.

Setup Context

  • Transferred settings (including Apple Wallet) from my iPhone 14 Pro
  • Cards from CIBC and Wealthsimple
  • Used SMS (not voice) as the second factor for verification

The Problem

After transfer, my cards appeared in Apple Wallet but still needed to be re-verified. Each time I tried SMS verification, the text code arrived and auto-filled into the Wallet app — but the “Next” button was greyed out.

On some attempts, the button turned blue, but tapping it did nothing. Result: I couldn’t verify or use my cards.

The Workaround

The fix was surprisingly simple: don’t rely on auto-fill.

  1. Request the SMS code as usual.
  2. Open the Messages app, copy the code manually, and paste it into Wallet.
  3. This time the “Next” button turned blue and worked, letting me add the cards.

Likely Cause

Based on testing, there may be a bug in iOS 26.0 where auto-filled SMS codes don’t properly trigger the Apple Wallet verification step. Until Apple fixes it, copying the code manually may help you get around the issue.

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Aside

2025.9.13

I’m looking forward to an iPhone upgrade year and leapfrogging to AirPods Pro 3 — hopefully this time I can get a good fit without needing third party ear tips!

I’m also curious about Apple’s new crossbody straps. Not for my phone — I haven’t used a case in years — but maybe as an adjustable strap for my smaller cameras.

There’s got to be someone who’ll review this use case, right? And if not… consider this my open call.

Categories
Photography Writing

Supporting Artistic Creativity

Back in February 2022, I made a commitment to myself. I set out to add a bit more positivity to the internet by reaching out to writers whose work inspired me, or photographers whose images resonated with me. I wanted to thank them for their efforts and let them know their work was appreciated.

Recognizing People Matters

It is all too common for people to move through life without peers, friends, or family recognizing the importance of their work or the ways they’ve shaped others’ lives. In my personal life, it was only after my father died that many of the kids he’d mentored reached out to me to share how he had positively affected the course of their lives. His Facebook feed was filled with comments from people who had benefitted from his generosity and kindness. But I was left wondering: had they ever told him directly about his impact? And if they had, might he have avoided his death of despair?

And I’ve seen the power of professional recognition–and felt the cost of its absence. Years ago, after a major project wrapped up, I realized I had forgotten to recognize the exemplary contribution of a junior staff member. I went back into the room to point out how critical their work had been. That small moment of recognition, as it turned out, had a profound impact on their career trajectory. And it was only after I left my last professional job that people contacted me from around Canada about how the work I produced had influenced them, their practice, and their thinking. I’ll be honest: when I left that job, I felt like I’d been writing into a void. Almost no one ever directly recognized the work I was producing or the value they placed in it.

Recognizing Creatives

On Glass, I try to leave a couple of comments on other photographers’ work each month. Sometimes those comments are short, like “Love the composition!👏👏👏 ,” or “Great use of tonality across the frame! 👏👏👏” Other times, when I have more bandwidth, I write longer, more substantive reflections on what I see in their images.

I think this kind of recognition matters. Too often, we wait until it’s too late to share it. Positive, explicit recognition can motivate people who may not have received much encouragement otherwise. It’s one of the many reasons why I support Neale James’ Photowalk Podcast and the community of kindness that he fosters with every single episode.

Lately I’ve been thinking about how to take this further. For me, the next step has been to begin collecting prints or zines from photographers whose work or practice I deeply admire. I’m not buying prints from the famous names you see in galleries–no Martin Parrs for me!–but photographers working in niches that speak to me. Owning their prints feels special. It’s not just me saying “great work,” it’s me saying, to them, “I value this enough to want it in my home.”

Ownership is a Kind of Intimacy

There are practical challenges with purchasing other people’s work. As we know, shipping expenses, cost of making physical artefacts, and the economic realities facing both buyers and artists can impede purchasing other creatives’ work. We can’t all afford to purchase prints regularly. But even buying one piece every year, every few years, or even once a decade can make a meaningful difference. It’s a way of supporting creativity and giving artists recognition that lasts.

What’s powerful about this isn’t only the financial support. It’s the intimacy of having someone’s work become part of your everyday life. Unlike a gallery exhibition, which is temporary and public, a print hanging in your home or office is permanent and personal. It shapes the space you live in, and every time you see it you’re reminded of the artist and the respect you have for their work.

That, to me, is one of the most profound ways we can support and recognize each other as creators. It’s something that I continue to do, and I appreciate the works of others that I have the privilege of viewing on a regular basis.

In closing, if a creator’s work inspires you then I’d strongly encourage you to leave a comment, send a note, or even consider acquiring a print. It might mean more than you know.