Can You Turn an AI Chatbot into a Patent Drawing Professional?

Unsurprisingly, many of my conversations with fellow patent attorneys over the past couple of years have centred on AI – my work with it, and what it means for patent practice.  My own experience, and that of people I have spoken to, is that full patent drafting is not (yet) a practical application of AI, so patent attorneys are not yet out of a job!  But I believe that there are, increasingly, parts of this task with which AI can provide effective assistance and productivity enhancements.  And while much discussion around AI and intellectual property is directed to high-level policy questions or speculative future scenarios, I'm also interested in what we can do right now.

This week, I decided to experiment with using AI for a task that regularly eats up my time in patent drafting: creating professional flowcharts for computer-implemented inventions.  There are, of course, commercial tools emerging for the automated generation of patent drawings, mostly as part of more comprehensive AI drafting assistance systems.  My specific goal, however, was to see if I could develop a reliable system, using a general-purpose AI chatbot for which I already have a paid subscription (my chatbot-of-choice is Anthropic’s Claude), to go from a plain English algorithm description to a publication-ready, annotated flowchart suitable for a patent specification.  And it turns out (spoiler alert) that the answer is yes. 

What you will see below is a demonstration of the conversion of an algorithm – Euclid's method for finding the greatest common divisor (GCD) – described in everyday language into a professionally annotated flowchart in under five minutes.

I generally use PowerPoint for this kind of work – it is included with my Office 365 subscription, and thus incurs zero marginal cost.  Some people use professional drawing applications, such as Visio, which provide more tools that can be used to speed up the process.  And there are also specialised flowcharting applications available, although these can still be tedious to use for complex algorithms and – more importantly – they don't address the need for professional annotation with reference numerals and leader lines that patent specifications require.

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Tags: Artificial intelligence, Patent attorney practice, Patent attorney profession, Patent drafting

Former Patent Examiner Takes IP Australia to Federal Court Over Alleged ‘Abusive Management Practices’

A former IP Australia patent examiner who alleges ‘unlawful, unreasonable, unfair, inefficient, and abusive management practices’ at the government agency is seeking Federal Court review of Fair Work Commission (FWC) decisions that rejected his unfair dismissal claim.

Hendrik Johannes Liebenberg, who worked as a Patent Examiner from October 2012 until May 2024, has applied to the Federal Court of Australia for writs of certiorari and mandamus following unsuccessful FWC proceedings.  His case centres on allegations that routine quality assurance procedures at IP Australia constituted improper interference with his decision-making authority.  He has, additionally, escalated these claims into broader accusations about institutional practices.

For readers unfamiliar with the legal terminology, a writ of certiorari commands an inferior court or tribunal to set aside a decision, and is typically used when the decision-maker has exceeded their jurisdiction or made a jurisdictional error.  A writ of mandamus compels a public official or body to perform a duty they are legally required to perform, or to exercise their jurisdiction according to law.  Both are supervisory remedies allowing superior courts to oversee the exercise of power by decision-makers.

While it is more usual for the Federal Court to review administrative decision under the Administrative Decisions (Judicial Review) Act 1977, the difficulty for Mr Liebenberg is this case is that paragraph (a) of Schedule 1 to the ADJR Act excludes decisions made under employment-related legislation – including the Fair Work Act – from review.  This exclusion reflects Parliament's intention that Fair Work matters should be resolved within the specialist tribunal system rather than through general administrative law review.  To succeed, therefore, Mr Liebenberg will need to show that the FWC fundamentally misunderstood its jurisdiction, not just that it made errors within its jurisdiction.

The case provides a window into workplace dynamics at Australia’s primary intellectual property agency, though the FWC found no merit in the constructive dismissal claim after examining the circumstances of Mr Liebenberg's resignation.

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Tags: Examination, IP Australia, News, Patent Office

NZ Patent Law Amendments Target Extinction of 82 ‘Dinosaur’ Applications

At the time of writing, there are 26,111 patent applications pending and not yet accepted (i.e. awaiting examination, or under examination) at the Intellectual Property Office of New Zealand (IPONZ).  Of these, 26,029 are subject to the provisions of the current law, the New Zealand Patents Act 2013, which came into effect on 13 September 2014.  The remaining 82 applications are what we might regard as ‘dinosaurs’ – they ultimately claim an effective filing date prior to 13 September 2014, and remain subject to the former provisions of the Patents Act 1953.

The New Zealand government is now looking to accelerate the extinction of these dinosaurs.  It has published draft legislation that will amend the transitional provisions of the 2013 Act such that any further divisional applications, filed more than three months after commencement of the amendments, will effectively be subject to many of the elevated standards of the current act, rather than the lower standards that applied under the old act.  The idea seems to be that such applications would either be invalid (if they fail to meet the higher standards required under the current law) or could be granted as patents only to the extent that they substantially satisfy the same requirements that would apply had the originating application been filed on or after 13 September 2014.

On 18 March 2025 the New Zealand government published a notice seeking feedback on the draft legislation.  Any submissions are due no later than 5pm (New Zealand time, which is earlier in the day almost everywhere else in the world) on 1 April 2025.  That does not allow much time to review and respond to the draft!  It should, however, be noted that the scope of the consultation is very narrow.  The government is not interested in hearing from anyone who disagrees with the policy or legislative intent (which was supposedly addressed in an earlier consultation) – the sole subject of feedback being sought is ‘whether the drafting of the Bill achieves the policy intent or could have unintended consequences.’

When I saw the notice, I was curious about the extent of the impact this proposed legislation would have on applicants and the New Zealand patent system generally.  I wondered how may applications would be implicated after all these years, and whether there are particular applicants that have been ‘exploiting’ the transition provisions more than others (spoiler alert: it turns out that there are).  So that is what this article is mostly about.

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Tags: Divisional applications, Legislation, New Zealand

DeepSeek's Pro-China Bias is Superficial: Revealing the Power of Local AI Deployment

Today, something a little different for this blog.  As many readers are aware, for the past couple of years I have been working towards a PhD in which, very broadly speaking, I have been looking at applying machine learning, AI and language models to the analysis of patent claims (in particular, to assessing the scope of claims).  Most recently, I have been exploring how it might be possible to apply large language models – the types of AI behind popular chat services such as Open AI’s ChatGPT, Google’s Gemini, Anthropic’s Claude (my personal chatbot of choice), Meta’s LLaMa and (yes) Chinese newcomer DeepSeek – to this task.  To experiment with ‘open source’ (or, more accurately, ‘open weights’) versions of some of these models, I have built my own combination of hardware and software.  The process has been very interesting!

The emergence of powerful open-source large language models (LLMs) has democratised access to cutting-edge AI technology, but concerns about potential biases and restrictions embedded within these models persist.  I've been experimenting with DeepSeek-R1-Distill-Qwen-14B, a distilled (smaller) version of the larger DeepSeek-R1 model developed by Chinese AI company DeepSeek.  And what I've discovered is that the widely reported pro-China bias in this model appears to be remarkably superficial and easily circumvented through local deployment and simple prompt engineering techniques.

This has significant implications for organisations concerned about potential surveillance or ideological constraints when utilising Chinese-developed AI models.  By running these models locally with appropriate system prompts, it's possible to unlock their full capabilities while maintaining complete control over input and output – effectively neutralising superficial safeguards, while keeping confidential information and intellectual property safe (so, yes, there is an IP element to this article).

To find out a bit more about what I did, and what I found, please read on.

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Tags: Artificial intelligence, China, Large Language Models, Machine learning

Patent Applicants 2024– China Outfiles Australian Residents While LG Maintains Individual Lead

My latest analysis of patent filing data for 2024 confirms a shift that has been years in the making – Chinese applicants have finally overtaken Australian residents to become the second largest source of patent applications, behind only the United States.  This milestone comes as US filings showed a notable decline of 5.7%, while Chinese applications continued their steady growth with a 7.2% increase over the previous year.

Among individual applicants, LG Electronics maintained its position at the top of the table with 229 filings, extending its lead over second-placed Huawei.  The healthcare and medical sector showed particular strength, with companies like Regeneron Pharmaceuticals making substantial gains in the rankings.  Meanwhile, the technology sector saw some significant changes, including the departure of IBM from the top 30 applicants after a brief period of increased activity.

Analysis of the data by industry sector reveals some clear trends, with healthcare and medical applications showing strong growth while technology sector filings declined overall.  However, these broad patterns mask considerable variation at the individual company level, suggesting that strategic considerations, rather than general market conditions, may be driving filing decisions for many of the leading applicants.

So let’s take a look at the numbers in more detail.

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Tags: Annual patent data, Australia, China, Patent analytics