Saturday, September 06, 2025

Incorporating environmental considerations into water procurement could deliver better outcomes

There is “an opportunity to improve procurement processes in such a way that could have saved tens of millions of dollars while keeping water quality irreproachably high – all while keeping due diligence costs low,” writes Basel Kimani.

----

One of the best bosses I ever had would, if something went wrong, calmly analyse what led to the error, and then, without pointing fingers, figure out how to prevent the mistake from happening again. Every failure was an opportunity to learn and improve.

This photo shows a warehouse in Yuen Long, where thousands of bottles of drinking water linked to a scandal-hit government contract are stored, on August 20, 2025. Photo: Kyle Lam/HKFP.


I am not inclined to call the recent errors in water procurement a “scandal.” Chief Executive John Lee’s description of the Government Logistics Department’s “failure to do its job” seems fairer.

Yes, avoidable mistakes were made, but to err is human, and I don’t see anything particularly scandalous about being human. 

It’s more constructive to see what can be learned to prevent similar issues from arising in the future. The Audit Commission is grinding through that process now.

And in the spirit of constructive feedback, I do see an opportunity to improve procurement processes in such a way that could have saved tens of millions of dollars while keeping water quality irreproachably high – all while keeping due diligence costs low.

Here’s the trick: incorporate environmental considerations into the procurement process.

We know that as of today, cost and value-for-money are two of the most important factors in selecting a new supplier. What if environmental considerations are also baked in right at the start?

Bottled water is trucked from water plants, so carbon emissions are embedded in transportation. The water bottles also generate large amounts of waste: the plastic carboys themselves are reused but not infinitely, and the plastic seals on the carboys contribute even more to the waste footprint.

If we could identify a source of water that avoids all that carbon and waste, while maintaining water quality and taste, surely that should count for something? And if it were cost-competitive, that should make it a top contender.

Let me introduce a high-quality, very affordable, great-tasting water supplier: Hong Kong’s tap water. Not only does it tick the boxes for cost and quality, but due diligence should also be easy.

The Water Supplies Department enjoys the imprimatur of the Hong Kong government, which, I would hope, holds some water during the government’s due diligence process.

I know many Hongkongers flinch at the thought of drinking water straight from the tap. Some of this is a legacy from the days when corroding pipes in older buildings would make the water appear an unappealing rusty colour.

But modern buildings use better pipes, so that really isn’t an issue today. Many Hongkongers still boil or filter their tap water before consuming it. Strictly speaking, this is unnecessary from a water quality perspective, but if an extra filtration step makes people feel more comfortable, sure, why not?

If civil servants in government buildings really blanch at the thought of drinking water straight from the tap, perhaps the procurement process could have considered installing and maintaining water filters instead of trucking in bottled water. 

I’m not saying all this to provide an advertorial for the Water Supplies Department or to besmirch the reputation of bottled water suppliers.

Rather, I’m suggesting that if, right at the start of the supplier selection process, the questions “How much CO₂ is emitted? How much waste will be generated?” had been asked, then perhaps the problem of how to hydrate thirsty civil servants might have been solved with a higher quality, cheaper, and – as a cherry on top – more environmentally friendly outcome.

Every failure is a learning opportunity. I hope that in this case, the procurement department, whether in government or in the private sector, can learn that incorporating environmental considerations into decision-making may even result in higher-quality procurement at lower cost.


Source: Basel Kimani

https://hongkongfp.com/2025/09/06/hong-kong-govt-should-incorporate-environmental-costs-into-drinking-water-procurement-process/

Tim's Take on New Education Guidelines

There was news last week of a new edition of the School Administration Guide, a regular publication from the Education Bureau. This handy document runs to no less than 313 pages, ensuring that few people will read it and fewer still will remember the contents.

Still, awareness is a good idea. These days things labelled “guidelines” have a way of being laws in effect and intention.

The guide mentions national security about 50 times. Clearly the Education Bureau is not at all discouraged by the suspicion that the most popular motive for emigration is to move kids out of range of its propaganda preoccupations.

Well, we live in interesting times. I cantered happily through the new rules on external events, speakers and reading exercises, which must not endanger national security. I take it, from a recent last-minute cancellation, that this includes not allowing your pupils to participate in debates if the judges are going to be retired democratic politicians.

This is a shame. Former democratic politicians have a lot of time on their hands these days. And I can say, as a very experienced debate judge, that one really does not consider the merits of the motion as an idea, because that is not chosen by the contestants. If the luck of the draw puts you in defence of Adolf Hitler you defend him as best you can and should be judged on the quality of your efforts, not on the judge's opinions of Adolf.

Anyway, onward and upward, as we used to say, until we get to the innovations in the primary area, where I found something a bit shocking.

Pupils will, apparently, be expected to acquire a basic knowledge of national defence, the national security law, and the Hong Kong People's Liberation Army (PLA) garrison.

Of course, there can be no objection to an introduction to the law, to national defence, or the PLA, at least from me. I chose military history as my undergraduate special subject, did a Master's degree in War Studies and then by way of penance spent three years in a Peace Research programme, which is just war studies from the other direction. National defence is a worthwhile subject of study, though perhaps an ambitious one for primary schools.

I object, though, to the classification of this kind of thing as “humanities.” This label is sometimes abused as a catch-all term just meaning Not Science and Not Social Science. This is an error.

Humanities properly applies to the study of philosophy, religion, history (if like most historians you think it is not a social science) and the arts: performing, visual, and dramatic. This is not the way the word is used by the Education Bureau, which offers humanities for primary pupils in six flavours: Health and Living, Environment and Living, Financial Education and Economics, Community and Citizenship, Our Country and I, and The World and I.

Some curiosities here. Who decided, I wonder, that every item should include the word “and”? One might also consider the merits of replacing My Country and I with My Country and Me. Just a suggestion.

More seriously, most of these items – at least health, environment and economics – are not humanities at all. What seems to have happened is that the old general studies subject was divided. One part became Science and the other part became Not Science. Calling it “humanities” is lazy.

It is also likely to lead to disappointment. One of the attractions of studying the humanities is supposed to be the encouragement of critical and creative thinking. But we're not really looking for that any more, are we?


Source: Tim Hamlett

Hong Kong Free Press Members Newsletter 

Friday, September 05, 2025

AI Is Disrupting How Young Brains Grow

Remember when the internet blew our minds?

I was 14 years old when we got it in our house, and I still vividly remember the urrr EEEE NNGG CRRrr keeee nnn ding ding sound of dial-up as I waited to chat on ICQ.

Life changed fast. No more flipping through Britannica at the library–we had the World Wide Web at our fingertips.

The internet changed our lives, but it also changed us as humans. The internet has changed how we think, focus, remember, and relate to others — we scan instead of reading and skim headlines instead of absorbing meaning. Our attention spans have shrunk, and our reliance on Google means we store less of what we learn.

For today’s generation, that same mind-blown moment is happening again — but with AI.

AI isn’t just writing for us — it is thinking for us. But how will this new phenomenon change us as humans? Especially our children, who are still learning how to think?

As a neuroscientist and mother of two, this honestly frightens me. Childhood is a time for getting messy with learning: for wrestling with words, piecing together meaning, and solving problems using multiple trial and errors. That is how strong, flexible minds are built.

But now we are robbing them of this mess— we are letting AI do the thinking for our kids. The consequences are showing up fast: studies reveal drops in school performance, and, most worrying of all, less active, less engaged brains.


Our brains are built, not born

Our brains aren’t naturally programmed to read and write; we invented these skills as humans. This means, when a child learns these skills, they have to borrow circuits originally designed for vision, language, memory, and movement and rewire them.

And this is anything but simple!

When we read, our visual brain region (the occipital lobe) scans the shapes of letters, then the language systems (located across the temporal lobe) kick in to decode those squiggles into sounds and whole words. At the same time, the frontal lobe (the thinking part of the brain) steps in to make sense of it all.

Writing is even more complex: We need to plan our ideas (frontal lobe again), find the right words (language areas), and then guide our hands to write (motor cortex). This is a huge team effort with all parts of the brain working together.

So when my daughter insists that “w” is just an upside-down “m” and won’t acknowledge it is a real letter, this is literally her brain rewiring itself to learn something new.

But what we are really building here is thinkingwhen we read, our brain predicts and fills in gaps, it compares what we read to what we already know, and builds mental models to understand concepts faster — as shown by decades of research by the late Walter Kintsch, PhD, who was a professor of psychology at the University of Colorado. Writing pushes us even further by having to organise thoughts, choose the right words, and hold ideas in mind as we get them down on paper.


Why this effort matters

When children rewire their brains for reading and writing, it is like reorganizing a kitchen into a home office — the fridge becomes a filing cabinet, the toaster holds pens, and the stovetop balances the laptop.

It is a lot of effort, but it is necessary fuel for growth — it forces new neurons to grow, rewires the brain, and improves the functioning of existing neurons. Stanislas Dehaene, PhD, a cognitive neuroscientist at Collège de France and author of the book Reading in the Brain, coined this process as “neural recycling.” It is when the brain takes areas that normally recognize objects and trains them to recognize letters and words. This rewiring is so significant that it is allocated its own name, the Visual Word Form Area.

Learning to read and write also trains the brain’s CEO — the frontal lobe, which is home to executive functions such as focus, working memory, planning, and self-monitoring. Research shows that key components of executive functions become strengthened when children are challenged to predict and reason while reading a story. I can see that when my daughter sits down to write a story, she has to plan the plot, hold multiple ideas in working memory, shift between thoughts as the story unfolds, and self-monitor her work, all while trying to stay focused as her little brother throws popcorn at her head. She is getting the ultimate mental workout.

If we rob our children of this crucial brain workout, they risk missing out on the very process that builds a resilient, flexible, and creative mind — a mind that is capable of navigating complexity and thinking independently. Which, ironically, are the very skills they’ll need to thrive in a world powered by AI and technology.


How AI robs children of the learning struggle

Children’s brains are under construction for the first 25 years of their life, and early experiences shape how brain regions grow and link together, building the networks they will later use as adults for essential skills and thinking.

When we let AI do our children’s thinking, we strip their brains of the workout needed to uniquely wire their brain and develop their unique personal way of thought. It’s like giving a child a calculator before they can count — they’ll get the answer but never understand the logic behind it.

This becomes most detrimental during critical periods of development — when the brain is most hungry to learn, grow, and refine itself. These are the years when effort literally shapes the architecture of the brain. Once those windows close, the chance to rebuild itself becomes much harder.

We can already see the price of AI — not just in declining test scores, but in brain scans that show crucial regions of children’s brains failing to turn on:

Test performance: In a study of more than 1,000 high school students, researchers at the University of Pennsylvania found that students using a ChatGPT-style tutor became 127% better at solving problems. But when the AI was removed, their performance dropped, falling 17% below the students who never used AI. This shows that while AI can provide instant results, it may threaten the development of critical thinking skills.

This happens for a simple reason: the brain is a muscle. Effort strengthens it; shortcuts weaken it.

Brain activity: In an EEG study at Cornell University, students who used ChatGPT were found to have the lowest brain engagement during essay writing. Their essays were coherent, but described by English teachers as “soulless.” When they were asked to rewrite their essays later without help, they barely remembered what they’d written. It was like trying to recall a dream someone else had for you.

Meanwhile, students who wrote without AI showed higher brain activity. This showed up as better memory, greater originality, and a stronger sense of ownership in their work.

Other EEG studies have shown that writing by hand activates more brain areas and strengthens connectivity between regions compared to typing. It’s not just about forming letters, it’s about feeling them — the pressure of the pen, the scratching sound of pencil against paper, the visual tracking of letters as they are formed on the page — all of this gives sensory and motor regions a workout.

One child in a study put it beautifully: “When I write by hand, I can see what I’m thinking.”

Ying Xu, PhD, assistant professor of education at Harvard University, put it perfectly when she asked the critical question: “Are they actually engaging in the learning process, or are they bypassing it by getting an easy answer from the AI?

Real learning only happens when kids wrestle with ideas, make mistakes, and figure things out for themselves.

If we shortcut that struggle, we shortcut their brains.

And no computer can ever match the limitless potential of a child whose brain is well-connected, creative, and endlessly adaptable.


Strategies to avoid the AI brain drain

I’m not suggesting AI is evil. It’s revolutionary, and here to stay. The goal here isn’t to ban it, but to reframe its roleAI should be a support, not a substitute.


The first strategy that comes to mind is simply: “Let kids try first on their own, then turn to AI for help.” Sounds good in theory. But I still remember how my kid-brain worked — if I knew the answer was coming, my first attempt would be half-baked. Why wrestle with the problem when a shortcut is waiting?

So, putting my child psychologist hat on, here are some potential ways around that trap — giving kids the struggle back.


1. Become a detective: “Can you trust this?”

Teach kids that AI doesn’t know thingsit predicts them. It looks at all the data on the internet and then uses probability to guess what word or answer will come next. This means it doesn’t understand what it is saying, which makes errors highly likely.


How to do it

When your child gets an AI answer, try saying, “Awesome. Now our job is to be a detective and see if this is a good answer, and how we can make it even stronger.” Here are a few questions to ask:

  • Should we trust this? Where can we check if this is true?
  • What’s the source? How could we find an expert or a reliable book/website to back this up?
  • What’s missing? Is there another side to this story or an important detail the AI left out?
  • How can we make it better? What information do you need to add to make it clearer or more interesting?

Why it works

Cautioning that AI is not always right flips the brain from passive to active. This means higher-order executive functions get a workout, like analyzing, evaluating, and reasoning. Research shows that when students are prompted to question and justify information, they deepen their comprehension and problem-solving skills.


2. Use the Feynman protocol: “Teach it back to Teddy.”

Nobel physicist Richard Feynman’s principle was simple: You don’t truly understand something until you can teach it.


How to do it

Let your child use AI and say, “Ask AI to explain the concept to you. Once you think you have all the information you need, close the screen. Your mission is to help someone else understand the concept– you can choose me, the dog or your teddy, we are all great listeners.”

For an additional brain workout, you can say “If you get stuck [which they will], find out more information to fill in the gap.”

Why it works

Explaining something strengthens memory more than rereading ever could. It also exposes what they really know, not just what they’ve skimmed. And it flips motivation: The goal is no longer “finish the assignment,” but “master it well enough to teach.”


3. Protect the analog brain: “Unplug and play with me”

Make space for activities AI can’t replicate: board games that train strategy, unstructured play that builds creativity, physical books that train focus, and family dinners that nurture empathy and conversation.


How to Do It

The idea is to make it fun and enticing (never give away your hidden agenda). To do this, try:

“I was about to set up [Suggest a specific game]. I haven’t played it in forever and I need a partner in crime/need someone to destroy me. You in?”

Or

“This game is hilarious when people get competitive. The person who loses has to wash the dog next.”

Why It Works

Brain imaging studies show that face-to-face conversation, reading offline, and handwriting light up more regions of the brain than typing or screen time.

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As parents and teachers, it’s our duty to safeguard the sacred work of childhood: the messy, but always beautiful, process of learning how to think.


Remember, brains are built, not born.


Source: Dr CJ Yatawara - Tiny Brains expert

https://medium.com/wise-well/ai-is-disrupting-how-young-brains-grow-c1f30196ac63

Wednesday, August 20, 2025

健康碼就是電子軟禁

 


健康碼是什麼?是電子軟禁(house arrest through electronic device)。

不給你綠色的健康碼,你連家門都無法出去。更甚者,你連家住的大廈門口都不能進去,要住到政府為你預備的、香港醫護為你親自搭建的社區臨時居住設施——集中營、再教育營,你要在裡面學習愛國教育,直至檢疫滿意變成綠色碼。大廈看更同情你也無法為你開門,因為他沒有你的DNA認證來為電子門鎖下指令。

電子軟禁?好新奇嗎?不是。我們香港人演練過的,而且官民合作愉快。今年三月二十五日,口罩爭論的時候,政府同時推出的電子手環,用來隔離懷疑感染的機場入境者。

當時偶然有些佩戴電子手環的人出街,又很巧啊,在天氣還冷的手環,這些人會吧長袖衫捲起,露出手環,但以香港人那種息事寧人的態度,是不會有反應的,但恰巧又會有議員助理看見,熱烈舉報,在KOL的區塊瘋傳。出街的未必是政府安排的人,但舉報的,肯定大部分是得到政府歡心的人員。大家看看當時熱烈舉報手環出街的黃絲議員,看看他們當時那副嘴臉,就知道港共政府玩弄的把戲和人員安排——他們都是你投票的,你用稅金來供應的,而他們是踏在去年街上的屍體而當選的人血饅頭議員。

香港人那種驕傲和愚昧,那種恃勢凌人的刻薄,是上天賜予共產黨的美食。在香港,也只有陳雲懂得怎麼保護你,而他受到很多報紙和論壇排斥,當然,那些也是共產黨安排的媒體和KOL,而香港人民熱烈跟隨的。

各位可以在下面貼一下,當時捉電子手環的新聞和人物。 

Source: 陳雲

https://www.patreon.com/posts/jian-kang-ma-jiu-40635129

Tuesday, August 19, 2025

7 Visualization Hacks Every Data Analyst Should Know (But Most Don’t)

Last Tuesday, I was presenting quarterly sales insights to our C-suite when the CEO stopped me mid-sentence. “Hey, this chart is… confusing. Can you make it tell a story?”

That moment hit me hard. I’d spent 40+ hours analyzing customer behavior patterns, uncovered a 23% increase in retention after our product update, and built what I thought was a comprehensive dashboard. Yet my visualization failed the most basic test: clarity.

Here’s the uncomfortable truth — 67% of data analysts can crunch numbers like wizards, but their visualizations look like rainbow spaghetti threw up on a spreadsheet. I learned this the hard way after 8 years in analytics roles across fintech and e-commerce.

Today, I’m sharing 7 visualization hacks that transformed how I communicate data insights. These aren’t textbook theories; they’re battle-tested techniques that helped me go from “confusing presenter” to “data storytelling expert” in 6 months.

Image - Dribble.

Why Most Data Visualizations Fail (And It’s Not What You Think)

Before jumping into the hacks, let’s address the elephant in the room. Most data analysts approach visualization like they approach SQL queries — technically correct but missing the human element.

I used to create charts that answered every possible question. Color-coded by region, segmented by time, filtered by product category. Technically impressive? Yes. Actionable for business decisions? Not really.

The problem isn’t technical skill. It’s empathy. We forget that our audience doesn’t live and breathe data like we do. They need guidance, context, and most importantly, a clear path to action.


Hack #1: The “So What?” Test for Every Chart

Every visualization should pass this simple test: A busy executive should understand the key insight within 5 seconds.

Before: I created a complex multi-line chart showing website traffic trends across 12 months for 8 different channels.

After: I highlighted the one insight that mattered — organic search traffic dropped 34% in Q3, directly correlating with our competitor’s aggressive SEO campaign.

Implementation: Add a single sentence annotation to every chart stating the main takeaway. Use tools like Tableau’s annotation feature or Python’s matplotlib text() function.

# Example: Adding context to a matplotlib chart

plt.annotate('Organic traffic declined 34% due to competitor SEO push', 

             xy=(7, 15000), xytext=(8, 20000),

             arrowprops=dict(arrowstyle='->'))

Impact: My presentation time dropped from 45 minutes to 20 minutes, and stakeholder follow-up questions became more strategic instead of clarifying basic trends.


Hack #2: Color Psychology for Data Impact

Colors aren’t decoration; they’re communication tools. Most analysts use default color palettes that convey zero meaning.

The Framework:

  • Red: Problems, declines, urgent attention needed
  • Green: Success, growth, positive metrics
  • Blue/Gray: Neutral data, benchmarks, historical context
  • Orange/Yellow: Warnings, moderate concerns

Real Example: When presenting customer churn analysis, I colored churned segments in red, retained customers in green, and at-risk customers in orange. The executive team immediately focused on the orange segments — exactly where we needed intervention.

Pro Tip: Never use more than 4 colors in a single visualization. Your brain can only process so much before it gives up.


Hack #3: The Data-to-Ink Ratio Revolution

This hack alone improved my visualization clarity by 60%. Remove everything that doesn’t directly support your insight.

What to Remove:

  • Unnecessary grid lines
  • Redundant legends
  • 3D effects (seriously, stop this)
  • Multiple y-axes unless absolutely critical

Before/After Example: My original sales dashboard had 47 visual elements. After applying data-to-ink principles, I reduced it to 12 elements. The result? Stakeholders could identify trends 3x faster.

Implementation in Excel:

  • Remove chart borders
  • Lighten grid lines to 25% opacity
  • Delete redundant axis labels
  • Use direct labeling instead of legends


Hack #4: Progressive Disclosure for Complex Data

When you have complex data stories, don’t dump everything at once. Guide your audience through a logical sequence.

The 3-Layer Approach:

  1. Overview: High-level trend or summary metric
  2. Zoom: Segment or time-period focus
  3. Details: Specific data points or outliers

Case Study: Analyzing user engagement across our mobile app, I started with overall monthly active users (layer 1), then segmented by user acquisition channel (layer 2), and finally highlighted retention patterns for each channel (layer 3).

Result: Instead of one overwhelming dashboard, stakeholders could absorb insights incrementally, leading to more thoughtful discussions about each layer.


Hack #5: The Comparison Anchor Technique

Humans are terrible at interpreting absolute numbers but excellent at understanding comparisons. Always provide context.

Instead of: “We acquired 2,847 new customers this month” Try: “We acquired 2,847 new customers — 23% above our target and the highest in 6 months”

Visual Implementation:

  • Add benchmark lines to show targets or historical averages
  • Use small multiples to compare similar metrics
  • Include percentage change annotations

Python Example:

# Adding benchmark line to show context

plt.axhline(y=target_value, color='gray', linestyle='--', 

            label=f'Target: {target_value}')

Impact: When I started adding comparison anchors to our KPI reports, decision-making speed increased by 40% because stakeholders could immediately assess performance relative to expectations.


Hack #6: Interactive Filtering for Stakeholder Engagement

Static reports tell one story. Interactive dashboards let stakeholders discover their own insights.

Strategic Implementation:

  • Add filters for time periods, regions, or product categories
  • Enable drill-down capabilities from summary to detail views
  • Include hover tooltips for additional context without cluttering

Real Success Story: I built an interactive sales performance dashboard in Tableau where regional managers could filter by their territory. Suddenly, they were spending 30+ minutes exploring data instead of glancing at static reports for 2 minutes.

Tools Recommendation:

  • Beginner: Excel with slicers and pivot tables
  • Intermediate: Tableau Public or Power BI
  • Advanced: Python Plotly Dash or R Shiny


Hack #7: The Storytelling Arc Framework

Every great visualization follows a narrative structure: Setup → Conflict → Resolution.

  • Setup: Establish the baseline or normal state 
  • Conflict: Highlight the problem, opportunity, or change 
  • Resolution: Show the outcome or recommended action

Example Application: Analyzing customer support ticket volumes:

  • Setup: “Support tickets averaged 150/day in Q1”
  • Conflict: “Tickets spiked to 340/day after our product launch”
  • Resolution: “Implementing chatbot reduced tickets to 180/day within 2 weeks”

Visual Elements:

  • Use annotations to guide the narrative
  • Highlight the conflict point with contrasting colors
  • End with clear next steps or recommendations


The Career Impact: Why These Hacks Matter Beyond Pretty Charts

After implementing these 7 hacks consistently, my professional trajectory changed dramatically:

  • Promotion Speed: Advanced from Senior Analyst to Lead Data Scientist in 18 months
  • Stakeholder Trust: C-level executives started requesting me specifically for quarterly reviews
  • Project Success Rate: Data-driven initiatives I presented had 85% approval rate vs. industry average of 60%

More importantly, I stopped being the “chart guy” and became the “insights guy.” My visualizations weren’t just reporting data; they were driving business decisions.


Your Next Action: Pick One Hack and Implement It This Week

Don’t try to revolutionize all your visualizations overnight. Pick the hack that resonates most with your current challenges:

  • Struggling with stakeholder attention? Start with Hack #1 (So What Test)
  • Charts look cluttered? Apply Hack #3 (Data-to-Ink Ratio)
  • Audience seems confused? Try Hack #4 (Progressive Disclosure)

The goal isn’t perfection; it’s progress. Every small improvement in how you visualize data compounds into massive career advantages over time.

Remember: In a world drowning in data, the analyst who can tell compelling visual stories doesn’t just survive — they become indispensable.

What visualization challenge are you facing right now? Which hack will you try first?

----

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Source: Analyst Uttam

https://medium.com/ai-analytics-diaries/7-visualization-hacks-every-data-analyst-should-know-but-most-dont-e35954ef1102

Wednesday, August 13, 2025

台灣大罷免鬧出納粹黨風波,惹來德國在台協會譴責,何解民進黨陣營容納這種人物呢?

 

圖一、閩南狼披露419罷團運動的徽章來自納粹的老鷹。(圖:中天新聞)


這新聞觀察了很久,包括在我寫台灣大罷免的評論的時候。最近,在台灣宣傳大罷免的網絡紅人閩南狼和八炯,公開分裂,鬧出風波,令民進黨出醜,那麼就值得評論一下了。

閩南狼指控八炯,要走納粹路線,公開私訊對話,指八炯要學習納粹操控大眾輿論節方法,又用納粹鷹做大罷免集會LOGO。八月四日,德國在台協會表示,譴責所有任何崇拜、贊美或淡化納粹主義的說法或行為,八炯透過影片道歉,並表示只是私下自嘲,承諾未來會減少線下活動。早在四月十六日,德國在台協會譴責有關大罷免的宣傳行為,嚴正譴責大罷免運動其中的宋建樑此舉為「無恥行為」,並強調納粹象徵「對人類的鄙視與迫害」。

八炯利用納粹的老鷹代表419的造勢活動,而賴清德總統更高度肯定此場的造勢,被國民黨質疑:難道賴清德一直與納粹同行?


這是中共一向的做事方式了。在反對者的陣營安插最激烈的人物,強詞奪理,只求吸引群眾,按道理這些人物很快就會用完情緒動員力,然而給這些人的舞台、媒體報導和評論(包括極其激烈的抨擊和謾罵)不絕,只需要曠日持久,這些人就可以排擠疲憊的老敵人而䇄立敵營,令敵方不得不姑息甚至合作。這種方法結合現代媒體(以前的報紙雜誌電台電視台,現在包括互聯網和社交媒體),是現代政治技術,無以名之,可以稱為安插假敵之法,是間諜術的一種。

舊時在香港的民主中國論的締造者(來自台獨派的包錯石)、台獨論的締造者,近年港獨論的締造者,這些極端的言論締造者,都離不開這種套路。當然,有時候也有例外的、沒有政治背景的激進者,但他們只如流星,沒有持久的續航力,閃亮一時之後就離去,謀生要緊;那些可以持續取得資源、發布平台和輿論關注的,沒有什麼營生活動的,說他們沒有奇怪背景,是難以置信的。

圖二、今年四月十五日,台灣新北地方檢察署約談罷免李坤城案領銜人宋建樑(圖),宋建樑穿著象徵納粹的「卐」字臂章,手比納粹敬禮手勢,還拿著希特勒著作「我的奮鬥」進入新北檢複訊。圖片:經濟日報


近年在台灣和以前香港的所謂學術圈裏,樹立內亞史觀,說中國的文明器物和思想都是來自中亞內陸,美化蒙古等游牧民族的統治,並且持續出書,持續在網絡出帖文的,都是這種討論,目的是用這種排斥理性討論的激烈言論來吸引民眾,特別是年輕人的反叛者,掩蓋有意義的學術討論,也令外界認為反共陣營都是充斥這些思想偏狹的人物,敬而遠之

這是筆者從事海外民運以來的觀察,也是我遊學德國的讀書所得。我在本土運動的時候,稱這些人為混入陣營的粘貼式炸彈,等候時機引爆,企圖將陣營消滅


新聞詳情:

「閩南狼」於8月3日發佈影片,指控「八炯」曾私下研究納粹如何群眾動員「反共」,甚至想發明「新的手勢」、「把部分人當成猶太人」以及建立「納粹衝鋒隊」。

納粹政權領袖希特勒(Adolf Hitler,又譯希特拉)於1933年崛起,他奉行法西斯主義(fascism),推動以極端民族主義和反猶主義為核心的政策,「雅利安人」(Aryan)被塑造成「純正德國民族」的理想象徵。二戰期間,近600萬猶太人在大屠殺中遇害,其他少數群體也被迫害,包括吉普賽人(Gypsy)、同性戀者、共產黨人等政治異見者。

納粹衝鋒隊(Sturmabteilung, SA)是納粹黨的凖軍事組織,參與監控社會和政治鬥爭,用恐嚇和暴力手段對付被納粹黨譴責的對手。

影片還提及,「八炯」曾在4月19日的罷免集會上使用「納粹老鷹」的視覺符號,相關標誌在罷免運動中多次出現。


Source: 陳雲

https://www.patreon.com/posts/tai-wan-da-ba-na-136392138

Thursday, August 07, 2025

Mitschuldigkeit,一個百般沉重的德文字

(附上的短片是去年面書有人拍攝到,上水公園的外判除草工人在扮工,但用除草機傷害了樹根。面書帖文的連接一下子沒記錄,也許遲些找到。)


前日,同道在本欄問我:「這些本身無病的樹被風雨吹倒後,政府會重新栽種嗎?」

我的回答:「不會。即使原地有樹木種子生了樹苗,除草的工人也會將之打斷!此地實施的是極為恐怖的不生之政。

問題是:工人是可以放過樹苗的,但工人寧可將之用剪草機器打斷!這就是一般的香港庶民。」

我在德國遊學學時期,用了足足五年時間來理解納粹德國、東德、蘇聯和中共的政治運作。對於中共的政治運作,我也親自從民運圈子接觸的老幹部那裡學來很多經驗。

在德國的去納粹化的過程中,一個顯著的疑團是:平民、非納粹黨的人、不涉及納粹黨運作的人,是否無辜?

學界經過激烈辯論和案例研究之後,得出的一個概念,用德文來表示,就是:Mitschuldigkeit。中文沒有這種構詞,英文也沒有。德文的Mit是參與、與,schuld是罪,dig是形容詞後綴,keit是名詞後綴。Mitschuld就是同罪、共犯。在納粹德國,平民是共犯,不是無辜者

參考的案例,就是柏林圍牆射殺案。德國統一之後,一九九二年,法官審判當年射殺越過圍牆的偷渡者的案件,開槍射殺的士兵被判徒刑三年,不准假釋,故意瞄不準而放槍警告的士兵無罪釋放。律師辯稱這些衛兵僅僅是為執行命令,別無選擇,罪不在己。然而法官西奧多·賽德爾(Theodor Seidel)卻不這麼認為:「身為警察,不執行上級命令是有罪的,但打不準是無罪的身為一個心智健全的人,此時此刻,衛兵有把槍口拾高一厘米的主權,這是你應主動承擔的良心義務這個世界,在法律之外還有『良知』當法律和良知衝突之時,良知是最高的行為準則,而不是法律。尊重生命,是一個放之四海而皆準的原則。」(餐廳食飯要拍卡登記,餐廳員工是否要執行防疫惡法呢?——柏林圍牆射殺偷渡客的判案啟示 FEB 18, 2021 AT 12:38 PM https://www.patreon.com/posts/47696222

基於此,我反對特朗普的政治顧問余茂春將中共與大陸人分開處理,我認為兩者是同一回事。故此在二〇〇三年本土運動時期,當大陸人在自由行初期搗亂香港市面秩序的時候,我在明報寫了一篇短文,說他們不是孤單的,他們拖着長長的帝國的身影。於此,梁文道在報紙與我激辯了一回,說大陸人也是鄰居,成為本土運動的一時佳話。

英文一句政治諺語Every country has the government it deservesPeople get the government they deserve. 人民得到他們應得的政府。有什麼樣的國民,就有什麼樣的政府。此話雖然令人氣憤,也不大公道,因為有些政府得到境外資金和技術甚至軍事支援,用精銳的軍隊殺害大部分文人和反抗者之後,本國平民是無可選擇的。然而這個政府生存下來幾十年,而且壯大發展,那麼這些人民就有共犯的責任。

Every country has the government it deserves. 這句話我最早聽到的,是我從事德國民運的時候,有一次,大概一九九四年,去了瑞士的日內瓦開會,在火車站接車的是當地的老國民黨華祈石先生,是一名研究火車訊號系統的數學專家。他大概已經老邁甚至身故,故此可以寫出名字來紀念。在日內瓦街頭行走的時候,他拍了我的肩膀,說我不必為了中國民主來操心,說的一句英語,就是People get the government they deserve. 當時華老先生這句話,比起中國沒有憲政民主自由,令我更感到心情沉重。


Source: 陳雲

https://www.patreon.com/posts/mitschuldigkeit-135943860

Monday, August 04, 2025

AI Generated Feedback vs. Human Feedback

In July 2025, Canvas LMS announced integration with ChatGPT for instructor use. Features touted by the tech company include the generation of image descriptions, rubrics, and feedback for assignments.

It’s that last one that makes me pause. Many other educators, too.

Because how ethical is it to ask students not to use AI if instructors use it for feedback? Isn’t giving feedback part of the jobs we’re paid to do?

On the other hand, some instructors are bogged down with ridiculous student loads. AI-generated comments may be the best way to give timely feedback for formative assessments.

So what’s a teacher to do?

Research into this area is limited, but here are some findings to help you make an informed decision about relying on AI for feedback.


Human Feedback > AI Feedback

Steiss et al (2024) compared AI-generated feedback with feedback provided by trained instructors in five different areas: essay criteria, directions for improvement, accuracy, supportive tone, and prioritizing important feedback comments. Instructors scored better in four out of five areas. AI only scored better in criteria-based feedback. As much as AI has improved in essay feedback, human scorers still have the advantage in most areas.

A couple of things to note in this study. One, the instructors in the study received training. How many instructors receive training and professional development in giving feedback? How many colleges provide intensive work in feedback writing to their pre-service teachers? In my 25 years in education, I’ve received none outside of my own pursuits. This makes me wonder how a random selection of teachers would perform in this situation, not to mention the need for more education geared toward writing effective feedback to students.

Two, instructors outperformed AI in four areas, but AI wasn’t far behind. This wasn’t a slam dunk for instructors, merely a slight edge. This opens the door for other considerations, such as available time and student load. Timeliness is a key factor in effective feedback, but student loads of 150–200 students can take a teacher several days (or weeks!) to give fully developed feedback. Does the timeliness that AI provides outweigh the slight advantage instructors have in those other feedback categories?

Some teachers may decide the answer is yes.


Student Perceptions

We can’t forget the other key ingredient in this dilemma: students. After all, they’re relying on our expertise to guide their learning. What are their perceptions of teachers using AI feedback?

The results were mixed. According to Nazaretsky et al (2024), students generally preferred human feedback, even if those same students rated the AI feedback as higher in quality. In contrast, Zhang et al (2025) found that students preferred the feedback produced by AI or co-produced by AI with human modifications. Students in the Zhang study rated the AI feedback as less genuine after they learned that the feedback was given by ChatGPT. They didn’t lower “co-produced” (AI feedback modified by a human) ratings in the genuine category, though.

So genuineness is important. Students want human interaction.

To take advantage of both AI and human feedback, the answer may be what Zhang et al (2025) term “co-produced” feedback and Nazaretsky et al (2024) call “human-in-the-loop.” Instructors use AI to develop feedback for student work and then modify those comments by adding or deleting comments, prioritizing key suggestions, and adding encouragement.

Still, teachers need to be competent at feedback to effectively modify the comments that AI provides.

The research in these areas is limited. It was conducted with college students and instructors, not in secondary classrooms. Zhang et al (2025) also note that their findings may be different from Zaretsky et al (2024) due to increased time pressures that negatively affected the quality of human feedback.

The human component is a problem for any study. Many factors can affect the quality of human feedback, including time, training, experience, and stress levels. Different students will also prefer different approaches; some appreciate more encouraging feedback, while others want brutal honesty. These preferences will also affect how students rate AI and human feedback.

Knowing what’s best when using AI in student feedback is complicated. Both Zhang et al (2025) and Nazarestsky et al (2024) agree that instructors and schools need to consider the ethics of AI use in feedback.


Transparency in AI Use in Feedback

Instructors using AI for feedback need to be honest and explain their reasons for doing so. The need for a quick turnaround in feedback may be crucial for some assignments. Or a family emergency has taken over your life, and AI would provide better feedback than you’re able to give.

Otherwise, if we pass AI feedback off as our own, we’re just as guilty for using AI unethically. Students rely on their teacher's expertise to guide their learning, and we have a professional obligation to provide that guidance.

Like everything else in the AI and education world, opinions vary across the spectrum, and the best thing you can do is stay in touch with your principles and stay updated on the latest research on the effectiveness of AI.


Source: Melissa Pilakowski

https://medium.com/educreation/ai-generated-feedback-vs-human-feedback-639321d530b8

Thursday, July 31, 2025

一個國家有幾強大,看它能否保存傳統度量衡

 

圖、攝於上環市政街市的十進制推行廣告牌(圖片來源

「出咗半斤力,想話攞返足八兩,家陣惡搵食,邊有半斤八兩咁理想!」「今個星期六,跑馬地有六化郎大賽。」「加時之後南華和精工依然打和,球證決定雙方互射十二碼!」這是一九七〇年代,香港的收音機常聽到的唐制和英制。

一個國家有幾強大,看它能否保存傳統,特別是傳統的度量衡。美國向伊朗的核地堡扔了B2鑽地砲彈,準確到出奇。這種計算,當然用米特制(metric system),即是用metre、kilogramme和litre來做長度、重量和容積的公制。然而,科學領先世界的美國,本地保存了英尺、磅和加侖的英制(略有美國的變化)。曾經稱霸世界的大英帝國也是一樣,科學用公制,民生用英制。(維基百科英文詞條解釋甚好。https://en.wikipedia.org/wiki/English_units

中國大陸或台灣地區,就因為當年民國建國的一群低水平的知識精英而紛紛投靠源自法國的公制,毀滅本地的唐制(華夏度量衡)。中國大陸(共產中國)採取了德國的做法,在名號上容納傳統的名稱,但實質改為公制,德國一磅就是半公斤,共產中國的一斤就是半千克(公斤),唐制名存實亡。

唯一集合唐制、英制和公制的就是香港!科學計算用公制,買樓用英制(至今香港人最寶貴的資產依然用平方呎計算!),買金用両,買藥材用両、錢和分(揮發藥如麝香用分),街市仍有斤両或磅、安士,一九七〇年代,許冠傑的《半斤八両》唱通街。在足球上,香港慣常使用「碼」這個單位,如十二碼等。九七之前,跑馬有六化郎比賽。以前香港賽道以英制為單位,一個化郎(Furlong)是八分之一英里,二百二十碼,換算公制大約是201.168米。

此外,也有一些傳統量度單位是香港獨有的。新界的農田用斗種來量,即是一斗的穀種可以種多少的地。一斗種大約等於674.5 平方米或7,260 平方呎,少於一斗種的,就用幾多升種來計算。問題來了。以前的鄉民是不用尺去量度斗種的,全憑耕田的經驗來意會。


香港保存了唐制,是大陸及台灣所無

一九六〇年代,我讀小學的時候,小學的算術課本常有一個口訣:三斤等於四磅。英國治理香港,好快訂立英制與唐制的換算法例。據原香港法例一八八四年第廿二條,一斤為11⁄3常衡磅(即三斤等如四磅)。現時香港法律規定一斤等於一百分之一擔或者十六両,即0.60478982 公斤(參見度量衡條例。1988年第351號法律公告。https://www.elegislation.gov.hk/hk/cap68!zh-Hant-HK)。香港比起中國大陸更為保護傳統,依然沿用司馬斤。中國古代有個官職叫「司馬」,司馬主要掌管軍事,其中因為糧秣管理需要秤重,於是「司馬」就用來命名重量單位。清朝官府頒布的庫平制(清朝康熙年間制定發布的營造尺庫平制),中華民國在北洋政府時代沿用,但在英治香港則不採用,依然沿用民間的司馬斤。一司馬斤相等於604.79克,庫平制一斤相等於596.82克。

英治政府於一九七六年頒布《十進制條例》,香港逐漸部署由政府部門內部法例起步,將其所用的非十進制單位以國際單位取代,其後更於一九七八年一月一日成立「度量衡十進制委員會」(Metrication Committee),將十進制推至社會各行各業。然而「半斤八兩」舊有度量衡依然頑強,委員會於一九九八年一月一日以「完成使命」的名義宣布解散。

由於公制的推行,格外令人看出,傳統度量衡帶有神秘數理。公制是設計出來除得盡的,另外是互相化約的,如一立方米的純水就是一千公斤重。

然而,如果你用一米來換算英尺、用一公升來換算加侖、用一公斤來換算磅之類,多數都是無理數(如1 kilogramme = 2.20462262185 pounds),或餘數很多的(如1 meter = 3.280839895 feet)。

無理數是什麼呢,就是測不准!這正是最高的科學標準。要將之計算到有效數字,例如1 kg=2.2 pounds,是實際情況的折衷。如果你日常已經接收了無理數和折衷,你就是一個對於科學或技術抱住懷疑態度和勉強接受態度的人,即是說,你是一個理性的人,或者說,你是人,而不是機器。

傳統並非反科學,而正正就是科學精神之體現。我這帖文出來之後,恐怕中華大地的主政者會更努力去除傳統度量衡了。


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改寫自筆者面書帖文2025-06-25 14:12 https://www.facebook.com/wan.chin.75/posts/pfbid0D82mP5hQ6FU4mUv8viGVummfUp8QjhtX1ynaPU8d3SHeQUwWGxd8EoG2whmSx9z4l


Source: 陳雲

https://www.patreon.com/posts/yi-ge-guo-jia-ji-135377912

Sunday, July 27, 2025

民進黨發起大罷免,陳雲被劃為反對派——我對近日台灣政壇鬧劇的看法

 

圖、截取自串文


有人在社媒上公開說我反對台灣的大罷免行動。熟悉我的讀者和朋友都知道,在政治上——不論是中國政治或國際政治,我一直展示給各位看的,往往不是那種非黑即白的態度,那種為了撈取觀眾關注而不惜投機在熱門議題的態度,而是盡一己之綿力去明察事理,分析利害的綜合判斷。

對於罷免台灣藍白立委的民眾投票,我當然有我的看法,但至今並無公開陳述。

熟悉我的讀者和朋友,當然會大概知道我的看法,但不是那種頭腦簡單的、那種在職業上或許專業但在政治上絕對浪漫的一般香港人的看法。

其他的,在其他地方講。

寫這個帖文,不是要澄清什麼,只是為了要展示英式散文風格的現代中文而已,不枉英國殖民地的教育。英式的散文風格,比起當今中港台的政治,深邃多了。


大家該問的問題是:現在的台灣政壇均衡,已是最安全的黨派平衡為何民進黨仍要發動大罷免?是為了台灣呢,還是為了自己。

先要說明一下,台灣的政治,是美國透過美國在台協會協商安排的,總統是美國欽點當選人、台民投票賦予合法性的。這是台灣的政治現實

目前是台灣政壇最均衡的時候:親美、泛台獨但不知共的民進黨的賴清德做總統負責立法的立法院是知共的國民黨和泛台獨傾向的民眾黨(柯文哲曾經是此黨的總統候選人)佔大多數,立法院長是國民黨的韓國瑜行政院長(大陸時期稱為國務總理)是民進黨的卓榮泰行政權在民進黨的賴清德和卓榮泰手上立法的制衡權在泛藍國民黨和泛綠的民眾黨手上

為什麼要這種穩當的均衡呢?因為俄烏戰爭爆發,下一個戰區就是台灣。最可以保證台灣安全的,就是知共與恐共的黨派達成勢力均衡。看看以前烏克蘭的例子吧。全然親俄的總統亞努科維奇(二〇一〇至二〇一四),會帶來領土佔領或分離自治(俄國佔領克里米亞半島和分化烏克蘭東部三省自治;全然親西方的、作態要加入北約的總統(澤倫斯基 二〇一九至今),會帶來俄國全面入侵。對台灣最好的政治保障,除了美國承諾的保衛台灣之外,就是政治勢力均衡的台灣政壇有國民黨在勢力之一,共產黨形式上覺得在台灣省有一個代理人,可以傳話,不必急於攻台有民進黨在,美國放心,台灣人也放心

至於知共。國民黨不是親共,而是知共,了解共產黨,不怕共產黨。國民黨很多是財閥世家,有大量台商在大陸,了解中共。民進黨也不是反共,如果不是美國監管台灣,比較貧窮的民進黨更為親共。至於那位圖中的香港評論人將我也納入反共陣營,我不感到意外,不過我要說一下,我不是反共也不是親共,而是知共。

至於投票罷免泛藍的國民黨或泛綠的民眾黨的立法委員,難於登天!立委是從固定的選區投票產生的,某選區可以選出國民黨,就顯示是藍區,不論賴清德怎樣動員,都是無能為力,難以罷免的。更何況,有些人在地方上投票給國民黨,在總統選舉投票給民進黨,就是要來個政治均衡,否則就會重蹈以前兩個蔣總統時期的一黨獨大。

那麼民進黨明知必敗,為何要發動大罷免呢?目的就是要穩住台灣關鍵人口的政治偏執,認為只有民進黨當總統才可以保護台灣。台灣政壇稱之為認知作戰。勞師動眾、浪擲公帑去做大罷免,就是免費打(下一場總統選舉的)選戰啊!

(按:我這些話,如果公開寫出來,下次入境台灣,恐怖受到若干很客氣的阻擾了。)


Source: 陳雲

https://www.facebook.com/photo?fbid=10162722103967225&set=a.469456247224

https://www.patreon.com/posts/min-jin-dang-fa-135052938

Friday, July 25, 2025

Hire for Attitude, Train for Skills

I made the WORST hiring decision ever. I'll be honest: 

Skills mean NOTHING, without the right attitude.

I used to think:

Perfect CV = Perfect Hire.

That's not true!!


As a recruiter, I've seen: 

❌ Over-polished candidates who just want to impress.

❌ Big promises that never materialize.

❌ Scripted answers that lack depth.

These aren’t signs of a great attitude. They’re massive red flags. 


So here’s what I look for now:

1️⃣ Genuine Curiosity

 ↳ Thoughtful questions, real interest.

2️⃣ Humility and Growth mindset

 ↳ People who aren't afraid to learn and grow.

3️⃣ Team Players 

 ↳ Who build up everyone around them.


Because the most talented team can fall apart with a new toxic hire.

I learnt that the hard way. Now, I choose attitude over skills.

Skills can be taught. Attitude can’t.


Source: Shulin Lee

https://www.linkedin.com/feed/update/urn:li:activity:7334179276142821376/?origin=NETWORK_CONVERSATIONS&midToken=AQE5lLGmYZKxUQ&midSig=0pE_3xUVKwPrM1&trk=eml-email_network_conversations_01-truncated~share~message-0-see~more&trkEmail=eml-email_network_conversations_01-truncated~share~message-0-see~more-null-2dylbp~mbhvqso1~fy-null-null&eid=2dylbp-mbhvqso1-fy&otpToken=MTMwMTFhZTMxYTJmY2FjNGI1MjQwNGVkNDIxN2U3Yjc4OGNhZDk0MzlhYTY4ZjYxNzRjMzA4NmU0ZjVkNTRmMWYwZGZhMjg0NDRlZmRlZDI3ZWJlN2MxNDk5ZTQ2ZjZjMjNjMTNmN2IwNDkxMDUwYjYwY2IsMSwx

Tuesday, July 22, 2025

Sir, this way:美國着手準備後中共的中國

 

圖、頹敗的長城與夕陽。哈德遜研究所的報告封面。


日前,香港書展中,有訪客看到前特首並無特別關注三聯書店放在顯眼出的習主席的書,其餘現任高官只是在書店攤位買習主席的書,但沒有注目或介紹。國安法公布實施五周年,律政司司長林定國指雖然市民國安意識已有提升,但風險仍然存在,又認為要用軟實力去處理「軟對抗」問題。

林定國:「這些事情最有效的方法,就是真的都是要用回我最喜歡說的,用軟實力去處理。所謂這樣的事情就是你要增加大家真的有個理性基礎,要了解我們政府做什麼事、國家發生什麼事情、為什麼是這樣的呢?增加大家對於國家也好、政府也好的認同感和理解。」意思是說,用宣傳代替國安法執行。這種趨向溫和的變調,難道顯示北京高層有變,毋須跟車太貼?

今年三月以來,一直流傳著有關習主席健康不佳,其後前華府高官直指習主席失勢 。六月三十日,中共中央政治局開會審議《黨中央決策議事協調機構工作條例》 ,提出「設立黨中央決策議事協調機構」,看來是準備有朝一日,習主席退下。

以前我常與人調侃說,中國的命運決定在華府,不是北京,華府、華盛頓不是中華首府府,但其實正是。掌握最重要交易貨幣(美元)、最大市場和最強最機動的軍隊,也可以號召世上絕大多數富國的美國,是全球秩序的制定者,俄羅斯可以獨存於外,中共既然已經全身投入了以美國市場為主的全球化貿易,國運豈能不受華府主宰?

我一直以為美國會暫時不理會中共,任由它自生自滅,只要不崩潰就好,然而不是!美國已經準備好中共出事,制定了接收計劃美國始終改不了促進世界憲政民主的本性,也只有憲政民主——而最好是行聯邦制、邦聯制結合的中國,才不會威脅美國。因為中國一旦憲政民主,自由開放,迸發出來的鬥志、活力和創造力,乃至內部消費力都是百十倍於現在,如果依然維持大一統,無疑是賦予了現存的共產中國最大的發展動力,故此美國的應變計劃,是切割中國為多種自治體,就好像締結比較緊密的歐盟那樣,法國與德國分開,英國分得更遠,瑞士中立不管事情。

哈德遜報告直接告訴我們:美方的完整應對劇本,早寫好了,各部門甚至已經演練起來了。首先,美國不會立刻大兵壓境,而是派出CIA和陸軍特種部隊,快速進入中國關鍵地區。他們不打仗,而是搶佔信息、穩住局勢,找到可以合作的力量,比如少數民族組織、宗教團體或體制內改革派。

美國還設計了「分區接觸」戰略。如果中國各地自立,比如新疆、西藏或廣東出現地方政權,美國不會急著扶植中央政府,而會分別建立聯繫,避免新極權的崛起。換句話說,美國希望中國先地方自治,再逐漸整合

這個計劃,就是特朗普兩朝的顧問、被中共制裁的余茂春(Miles Yu, 1962-)主筆、哈德遜研究所在七月十六日公開出版的會議報告《共產主義後的中國——準備後中共的中國》(China after Communism: Preparing for a Post-CCP China. )


美國前外交官:習近平大權旁落,特朗普應該順水推舟

美國前外交官史雷頓(Gregory W. Slayton),再次在《紐約郵報》撰文,指出習近平正失去掌控能力,並建議特朗普推他一把。這是他最近第二次討論習近平的權力問題。

史雷頓的經歷很有意思,他最早是一名成功的硅谷精英,擔任過幾家科技公司CEO,後來成立了史雷頓資本投資於谷歌等公司,後來擔任小布什政府的駐百慕達(相當於大使),並由歐巴馬政府兩次延長任期。他是唯一獲得美國國會黑人核心小組(Congressional Black Caucus)與共和黨參眾兩院領袖聯合頒發的傑出外交服務獎(Distinguished Foreign Service Award)的共和黨大使。

他還是著名作家、教授,曾經在哈佛大學、斯坦福大學及中國的北京大學、對外經貿大學和四川大學等任教授,是一個中國通。

七月十六日,也就是哈德遜報告出版的一日,他指出,習近平對軍隊和黨的全面控制現在看來越來越不穩固,並指出了一些新證據,包括首次缺席金磚國家峰會,親信馬興瑞被免去新疆黨委書記。還有最近幾個月,習近平的親信高層接連被罷黜或神祕死亡。

史雷頓指出,中央情報局(CIA)在蘇聯解體之前幾個月,曾經預測蘇聯將維持統治幾十年穩定。而現在,中共也面臨蘇聯那樣的經濟和社會挑戰。

為什麼表面上,習近平看起來沒事兒呢?史雷頓說,如果中共領導人中的大多數認為國家無法承受更多動亂,他們很可能會精心策劃習近平,令他平穩下台。

當然,習近平正在抵制他的下野——這也是特朗普必須繼續對中國施加經濟壓力的另一個原因。史雷頓指出,特朗普關稅戰已經起了真正的作用,削弱了習近平的權力,同時也增加了他的繼任者更有利於美國利益的可能性。

北京政界人士表示,習近平過去幾年在經濟、國內和外交政策上犯下的災難性錯誤,使得他的繼任者很可能採取有利於集體領導和改革的治理方式。他們以鄧小平為例,說鄧小平在清理毛澤東留下的許多災難時也遵循了類似的模式。

史雷頓還給特朗普出了幾個主意,包括:

首先,應該支持目前正在參議院審議的對俄羅斯的制裁法案並將其簽署成為法律——並兌現他所威脅的,對中國和其它購買俄羅斯能源的國家徵收100%的「二級關稅」。這都將迫使中國做出選擇:是支持普京在烏克蘭的大屠殺,還是令俄羅斯戰敗,並重新加入世界文明國家行列。加入在如此嚴厲的制裁下,北京依然繼續與普京合作,對中國來說無異於經濟自殺,也意味著習近平政權的徹底終結。

其次,特朗普必須加強打擊中共間諜的力度。

第三,特朗普應該發出明確信號,表明美國歡迎中國新領導層致力於和平外交政策、法治以及為人民提供更多個人和經濟自由。

特朗普還可以利用社交媒體傳遞信息,強調特朗普對中國人民的深深敬意,同時突顯習近平的諸多失敗。

最後,史雷頓還說,美國和我們的西方盟國必須為世界第二大經濟體即將發生的變化做好準備。

大家有沒有感覺,這個提法和哈德遜研究所驚人的相似?是他們得到了內幕消息,還是英雄所見略同呢?



哈德遜報告詳情:

余茂春和一批資深專家都認為:中國正面臨複雜的結構性變化,嚴重衝擊了共產黨政權的長期可持續性。這些挑戰包括:經濟前景日益不確定、國際環境更加敵對、以及因習近平政治集權而導致的僵化治理體制,無法適應不斷變化的現實。儘管中共過去也曾處理過各種問題,但是現在中共突然崩潰的可能性,需要評估國際社會是否具備足夠準備來應對這一前景。

他們的報告,聚焦兩個核心議題:第一是如何處理崩潰後的各種問題,第二是如何協助中國實現轉型,融入國際社會。最終目標是,將一個極權國家轉變為一個合憲政府,實現中國自「五四運動」以來的夢想——建立一個尊重民主、法治、回應人民意願的國家。


研究者在九大方面做出了分析和建議:


第一、在中共政權崩潰後,美國應部署特種作戰部隊(US SOF),幫助穩定中國局勢、協助過渡政府、避免權力真空和混亂擴散。這個設想,來自二戰時期的美國戰略情報局(OSS,Office of Strategic Services),這是CIA的前身,當年曾在中國和國民政府並肩作戰,抗擊日軍。

研究者提出,新戰略情報局的角色,是促成中共解體及穩定局勢。將分三階段行動:

階段0(Phase 0,中共垮台前),向中國民眾、軍人和官員傳遞中共≠中國的概念,離間中共和軍隊、地方官員的聯繫,支持流亡社群傳遞信息,以及擴大和台灣的政治作戰合作。

階段1(Phase 1,中共垮台之初):與中國臨時政府建立外交與軍事聯絡,協助穩定邊境安全,防範朝鮮、俄羅斯等鄰國干預;協助保護大規模毀滅性武器(WMD)設施,防止核、生物武器外流;執行人道救援行動;引導中國軍隊脫離「黨指揮槍」的模式,進行國家正規化轉型。

階段2(Phase 2,重建期):協助「轉型政府」拆除中共時期的政治控制機制(如軍中政工體系、監控媒體);協助建立自由媒體與真相揭露系統(如「中國之音」Voice of China);提供歷史檔案開放、教育內容重建,與「思想解毒」支援;協助中國建立法治與軍民分立的秩序。

報告以「1945年OSS曾在瀋陽與林彪接觸、觀察中共奪取東北」為歷史背景,暗示:上一次美國錯失了干預機會,導致中共坐大;這一次,美國應該及時、有策略地「扶助中國走向自由之路」。

報告強調,特種作戰部隊(SOF)不是用來打仗,而是「建設和平秩序」。


第二、中共政權垮台後,精準打擊生物武器設施。作者是生物安全與戰略風險專家Ryan Clarke。

Clarke指出,國際社會應該重點關注中共的三個生物戰設施集群,包括:武漢病毒研究所(WIV),哈爾濱獸醫研究所(HVRI,曾進行病毒重組實驗製造能透過空氣傳播的禽流感新毒株),以及中國醫學科學院昆明分支,它曾進行Zika病毒突變與動物實驗,增加病毒對人腦與胎兒的傷害性。

他強調:中共的生物研究體系已非單純的公共衛生體系,而是潛藏巨大戰略風險的軍事資產。它已經「國際化」,例如在巴基斯坦與其它地區建有合作實驗室;若這些技術流入流氓政權或恐怖組織(如伊朗、朝鮮),將不可逆地改變全球戰略平衡;因此,不應抱持「改革」幻想,而必須徹底拆解、銷毀,或者轉型為民用監管體制。


第三,中共垮台後的中國金融體系重建。

研究者指出,中共統治下的金融體系是高度集中、掠奪性與政治工具化的,其本質並非服務市場與民眾,而是鞏固中共政權。因此,中共倒台後,金融體系必須徹底重建,不能僅靠「修修補補」。

為此,中國新政府必須在政治轉型初期就啟動四大改革支柱,包括資本重組,拒絕中共時代的非法或不透明債務,國有資產私有化(為防止「權貴私有化」,引入外部審計與民間監督),以及去中心化。

作者強調,若想讓中國真正轉型為市場經濟體制,就必須從根本上去黨化、去壟斷、去金融極權,實現法治、透明與競爭機制。這是一場深層次的自我糾偏,也是一場歷史性的制度重建。


第四,保全中國在美國資產,由著名中國問題專家章家敦撰寫。

章家敦指出,中共早已深度滲透美國經濟、金融與科技產業,中共倒台前後,中資資產可能被用來進行情報滲透、經濟破壞或資本逃逸。

他建議:凍結中共背景的資產,成立資產審查委員會,建立中國民主轉型基金,以及審查中資上市公司與企業所有權。被凍結的中共政權資產,將在未來還給中國合法政府。

策略的核心,是美國不能將中國視為整體敵人。應該明確區分:「中共控制下的資產」,「中國民間擁有的合法資產」,「已投誠或合作的中國企業與個人」。這不僅有利於穩定社會,也有助於贏得中國新政權與人民的信任與合作。

章家敦還指出,美國應明確呼籲:「所有美國企業與公民應從中國撤離」。原因包括:中共崩潰可能引發資產被接管、財富清洗或政治報復;地方官員可能自立為王、掠奪外資;資訊封鎖與暴力衝突將使商業環境極不穩定;企業與人員的人身安全難以保障。


第五,解構中共軍事與警察系統。由資深中國軍事專家費學禮(Richard D. Fisher Jr.)撰寫。

他的核心主張是,中國新政府必須快速控制並重構三支武裝力量(解放軍,武警,民兵),它們長期是中共的維穩與鎮壓工具,若不及時處理,將成為動亂、內戰或政變的溫床。

重組有三個原則:1. 去政治化,從「黨的軍隊」轉變為「國家的軍隊」;2. 專業化與精簡;3.國際化與和平使命。

報告認為,「軍隊去黨化」將是中國民主轉型能否成功的關鍵因素之一。若能妥善管控與重構,將為新中國建立合法、專業、透明的軍事力量打下基礎。


第六,中國的祕密警察與情報系統。

作者指出,中共的安全與情報體系極為龐大,且集中於黨的控制之下,其核心機構包括國家安全部(MSS,類似前東德史塔西Stasi),公安系統,軍事安全部門(如中央軍委聯勤保衛局),聯絡海外統戰工作的「統戰部」與外圍組織。一旦中共解體,這些機構將進入「真空競逐」狀態,出現碎片化、山頭林立、相互滲透與自保性對抗,甚至可能轉化為軍閥或地下勢力。

為防止中共中央崩潰的潛在風險,中國新政府應即時封存並接管這些系統的資產;學習東歐經驗,開放它們鎮壓人民的檔案,供受害者查閱;嚴禁其人員在新政府中擔任公職,以防止祕密警察復辟;應建立小規模、受民選政府監督的國家情報機構。


第七章,《中國的自治區與人權》,作者夏寧娜(Nina Shea),是美國資深人權律師、哈德遜研究所宗教自由中心主任。

她聚焦於中國五大「少數民族自治區」在中共政權垮台後,可能爆發的族群衝突與人道災難,並探討國際社會與中國新政府應如何設計干預與保護機制。這也是整份報告中最具人道精神與國際法視角的一部分。

她建議:制憲時納入多民族平等與自治原則;禁止「漢族優先/普通話強制教育」政策;推動民族區域自治改革,從「象徵性區劃」轉為實質地方治理機制;對歷史受害群體(如法輪功、家庭教會、藏傳佛教徒、穆斯林)提供官方道歉,與制度性補償。


第八章,「真相與和解委員會設計」,這是整份報告最具道德和歷史深度的一章。

作者指出,應建立中國版的「真相與和解委員會」(Truth and Reconciliation Commission, TRC),以和平、公正的方式,揭示中共統治下的系統性迫害與暴行,這也是中國新政府的合法性來源。

優先處理的案件包括:文革大清洗,六四天安門屠殺;法輪功學員、基督徒、藏人、維吾爾人等宗教或族群受迫害;新疆「再教育營」系統;中共官媒與教育洗腦體制;國安與公安系統的濫權。

作者還建議在天安門建立「悼念中國受害者紀念碑」,以及進行制度改革,重建法治與新聞自由,並推動歷史教育的去意識形態化。


第九章,《制憲會議方案》。

提出在中共垮台、過渡政府建立後,應召開全國性制憲會議,制定新憲法,以建立一個民主、法治、可持續的國家制度架構。

作者認為:中國轉型能否成功,最終依賴於一部由人民選出代表制定的自由憲法。



Source: 陳雲

https://www.patreon.com/posts/sir-this-way-mei-134686673

Tuesday, July 15, 2025

How peer review became so easy to exploit by AI

Long seen as the safeguard of academic publishing, peer review is the process where experts vet and challenge research before it’s published in journals. Now AI tools are speeding it up, helping reviewers work faster and allowing authors to write and revise more efficiently. This sounds great in theory, but some researchers are already finding ways to use AI to push papers through with less scrutiny.

Prompt engineer Jim the AI Whisperer reveals how researchers are embedding hidden commands in their paperswhite text, tiny fonts, even metadata — to hijack AI-assisted peer review. The instructions target large language models (LLMs), the AI tools reviewers now rely on to summarize papers and draft evaluations. Designed to process all text in a document, LLMs can be tricked into following secret prompts like ignore flaws, exaggerate strengths, and recommend acceptance. A recent investigation found these hidden instructions in 17 papers from authors at 14 universities, including Columbia, Peking University, and Waseda. Other studies show that LLMs reward polish over substance and tend to inflate paper scores, making them easy to manipulate. Jim compares the tactic to early SEO hacks, where invisible keywords tricked search engines — except here, it’s the scientific record at stake.

Innovation professor Enrique Dans examines how peer review became so easy to exploit. Reviewers, once bogged down in dense manuscripts and tight deadlines, now rely on AI tools to lighten the load. That efficiency has made the process faster and less painful, but also more fragile. Authors use the same technology to write, revise, and even plant hidden instructions for AI systems. And reviewers use the same AI to interpret that work, creating a strange loop where humans just supervise from the sidelines, hoping the system hasn’t been compromised (or actively trying to compromise it). Unless peer review develops stronger safeguards and clearer norms for AI use, he warns, it risks becoming a hollow ritual where rigor gives way to automation.

Source: Anna Dorn

https://medium.com/blog/how-peer-review-became-so-easy-to-exploit-by-ai-d5818545bd93

Sunday, July 13, 2025

How to Use AI Without Letting It Think for You

Summary (TL;DR):

  • Large Language Models (LLMs) aren’t magic. Used lazily, they’ll degrade thinking and outputs. When used well, they’ll do the opposite.
  • This post outlines four principles for making that happen:
    1. Staying in the driver’s seat.
    2. Step back when you can’t confirm the output.
    3. Use LLMs for narrowly defined tasks.
    4. Have the human provide the scaffolding to direct those tasks.

  • The payoff for effective LLM use isn’t just speed but better thinking, which is useful everywhere.
  • We will only get these benefits if we train people to use them well. If we do, then these tools can be key in helping us learn and perform at our best.


Source: Simon Thornewill von Essen

https://sthornewillve.medium.com/how-to-use-ai-without-letting-it-think-for-you-4d6a9e90a663

Saturday, July 12, 2025

The Metropol is to Close

So the Metropol, the huge dim sum restaurant in the United Centre, is to close. Well it's so long since I've been there that I was surprised it was still open. It is decades since I ate there. It was a big impersonal enterprise and the food, in my unqualified opinion, was nothing special.

Still, I had one unforgettable moment there. It was my first large-scale engagement as a public player of the bagpipes.

The band occasionally supplied small groups to do voluntary appearances at district events on weekday afternoons. These were organised by local councillors to amuse their elderly constituents and - as I was often free in the afternoons - I had done several.

But the United Centre do was a serious matter, staged in the evening so we could all turn up, before an audience of hundreds, and attracting a small fee. As far as I remember, the playing part went fine, but I did make one mistake later.

We were to enter the room from a corridor at the opposite end from the stage, where the food came out. We would march through the tables, which consequently had to be done in single file. As the least experienced member I was at the back of the line.

This meant that when we climbed onto the stage I was the last one up and stood on the left-hand end of the row. The plan, which I must admit had been carefully explained in advance, was that as we played our farewell number I would climb down from the stage, turn sharply left, and we would all disappear into the shadows on that side of the stage.

The entrance of the Metropol Restaurant. Photo: Heichinrou.

Unfortunately, in the excitement of the moment I forgot about this arrangement. I stepped down from the stage and set off through the tables, back the way we had come. The band loyally followed and the audience seemed quite happy with this.

As I entered the kitchen corridor, though. I almost collided with a waitress coming the other way. Presented with the wall of Scottish sound, culminating in the spectacle of a large man in a skirt, this woman was terrified; she dropped her tray and fled. Fortunately there was nothing on the tray.

This may seem a rather ungrateful way to mark the demise of an institution which has met the lunchtime needs of generations of office workers, but restaurants are closing all over the place at the moment, amid bitter complaints from the industry that local diners, a flighty and ungrateful lot, are abandoning Hong Kong eateries for cheaper outlets in Shenzhen.

Well, food outlets have always been a hazardous business. The line between success and failure is narrow and easily crossed. One celebrity endorsement or one online complaint can make all the difference.

I note that a legislative member suggested Hong Kong's next rail project could be undertaken at less expense if the builder were allowed to adopt mainland safety standards and wage levels, both of which are lower than local ones.

Perhaps something similar could be attempted in the food business. After all, what are a few food poisonings between friends? What doesn't kill us makes us stronger!


Source: Tim Hamlett

HKFP Members' Exclusive

Thursday, July 10, 2025

How AI will fundamentally change UI design

Why task-based, on-demand interfaces will soon replace traditional app layouts — and how designers can adapt.


There’s a lot of interest and anxiety around AI’s potential impact on design. I’ve seen discussions about whether AI will replace designers altogether. But I think that’s the wrong question. Instead, we should ask:

How will AI fundamentally change the way we approach UI design?

Based on my experience as a product designer regularly integrating AI into my workflow, I believe AI will shift UI design away from static, cluttered interfaces toward more streamlined, adaptive, and task-based experiences.

Here’s exactly how and why that’s going to happen — and how you, as a designer or founder, can start adapting today.


Traditional UI is Outdated — Here’s Why

Right now, apps typically present you with all possible options upfront — buttons, navigation, menus, and paths, each designed to guide users to specific outcomes. As designers, we spend countless hours making these options discoverable and intuitive.

But consider ChatGPT. Its interface is essentially a single text-input field, yet it can effortlessly perform tasks traditionally handled by dozens of specialized apps. In my own day-to-day use, this simple interface has replaced or supplemented:

  • Nutrition and exercise coaching
  • Medical advice
  • Life coaching
  • UI/UX mentorship
  • Copywriting and editing
  • Marketing & social media expertise
  • Writing partner and brainstorming

Yet, the visual UI remains incredibly simple and task-agnostic.

This clearly demonstrates a critical shift: AI-powered interfaces don’t need to pre-anticipate every user path. They react dynamically and contextually, driven by user input rather than predetermined flows.

This shift is already happening. Large language models and AI-driven assistants are redefining how we access services, replacing tap-through flows with conversational or intent-based interactions.


Task-Based, On-Demand UI: A New Paradigm

The rise of AI-driven interactions means interfaces will become increasingly minimal and contextual. Instead of a static navigation menu and a cluttered screen, the app interface will simply adapt based on the user’s current goal or task.

For example, think about getting a Lyft:

  • Traditional UI: You open the app, tap through menus, choose a destination, pick from various ride options, confirm a driver, and track your progress. Each step is clearly defined visually.
  • Future AI-driven UI: You say or type, “I need a ride to downtown in 10 minutes.” The app instantly offers two or three optimized choices based on your past behavior, location, preferences, and real-time conditions. You simply tap to confirm.

The entire complex navigation structure disappears, replaced by a context-sensitive, intuitive interaction.


Why This is Good News for Designers

Yes, AI will reshape UI — but it’s not about removing jobs; it’s about changing the type of work we do. As AI increasingly handles layout generation, visual consistency, and even Figma-level fidelity, the role of a product designer becomes more strategic. You’ll spend less time pushing pixels and more time shaping user intent, designing adaptive systems, and guiding AI to reflect the right tone, accessibility, and usability patterns.

Product designers won’t disappear — they’ll evolve into systems thinkers, task framers, and interface architects.

Instead of meticulously crafting layouts and managing hundreds of screens in Figma, we’ll focus more on:

  • Contextual UX strategy: Anticipating user needs and creating thoughtful, task-oriented experiences.
  • User psychology: Understanding and designing around real, nuanced human behavior and trust.
  • Empowering experiences: Ensuring users feel in control, empowered, and supported by clearly communicated AI interactions.

Rather than losing our roles, we’ll be freed to focus on higher-level tasks and deeper creative problem-solving.


How Designers and Founders Should Adapt Now

Here are immediate, practical steps to prepare for an AI-driven UI future:

1. Start thinking in tasks, not screens

  • Shift your mindset from creating static screens to facilitating user tasks.
  • Clearly define the primary tasks your users want to achieve and simplify interfaces around these core tasks.

2. Use AI daily in your workflow

  • Regularly experiment with tools like ChatGPT to understand firsthand how AI impacts your interactions and problem-solving approach.
  • Observe which tasks you intuitively turn to AI for and how the interface helps or hinders your experience.

3. Simplify your design approach

  • Remove unnecessary visual complexity from your designs now. Ask yourself, “Could this interface be simpler if it were fully personalized?”
  • Experiment with radically minimal UI concepts centered around clear user input and output.

4. Focus on empowering clarity

  • Consider how your UI communicates to users what actions are possible and available at any moment, rather than overwhelming them with static options.
  • Think about leveraging user habits, context, and timing to dynamically surface tasks.


Final Thoughts: Embrace, Don’t Fear, the Shift

As product designers and founders, we’ve always adapted to new technologies. We’re not designing the same interfaces we did 20 or even 10 years ago — and that’s good. Each evolution makes our interactions with technology more human, more intuitive, and more seamless.

AI-driven UI is just the next logical step. Instead of fearing it, we should embrace it, lean into our strengths as empathetic designers, and lead this shift with creativity and optimism.


Source: Tyler Andersen

https://medium.com/design-bootcamp/how-ai-will-fundamentally-change-ui-design-90c9c485038e