If we are serious about “ensuring U.S. technology and U.S. standards — particularly in AI, biotech, and quantum computing — drive the world forward,” then we have to treat these domains the way earlier generations treated nuclear deterrence and space: as whole of nation, long cycle industrial and security projects, not a loose collection of R&D programs, underwriting legacy companies and venture bets.

That implies three concrete shifts.

First, we need a disciplined technology portfolio, not a wish list. AI, compute, networking, sensing, energy, and advanced manufacturing form one interdependent stack. A policy that overindexes on model development while underinvesting in chips, power, networking, and secure software supply chains is strategically incoherent. A credible strategy must specify where we intend to lead absolutely, where we are content with allied parity, and where we are willing to trade or depend.

Second, the defense industrial base must evolve from a small-batch, platform-centric model to a software-driven, high-iteration, and update-centric ecosystem. The NSS is right to call out the cost asymmetry between cheap offensive drones and expensive defensive systems; the response must be sustained investment in automation, AI-assisted design and testing, and dual-use manufacturing capacity that can surge on demand.

Finally, we must institutionalize public–private collaboration at operational tempo, not conference tempo. The most important emerging technologies now live exclusively in the commercial sector. That requires new mechanisms for classified problem sharing, streamlined security accreditation, and procurement pathways measured in months, not years.

In strategic technologies, time is now the decisive variable. Our investments should be judged less by dollars committed and more by how quickly they change what our operators, analysts, and allies can do. The clock is ticking.

—

This originally was published here in response to the new US National Security Strategy

Certainly, the familiar Trump agenda items that consumed much oxygen during the first presidential run will reappear as encores—flashy tax cuts (that don’t pay for themselves), fresh trade war saber-rattling (be ready to hear more about Tariffs), and doubled-down on drilling & energy independence / export. Supporters and critics alike can expect more of the same script that fuels Trump’s uneven political strengths while inflaming the cultural divides his detractors decry as tearing at the fabric of American unity. Hence for Trump part two, the underappreciated chances he takes sculpting smarter guardrails around innovational forces like AI and crypto—modern innovations promising (and delivering!)  both economic boons and societal disruption—may ultimately determine the overall reception of his leadership as polarizing or prophetic.

But separate from the trifecta of taxes, trade and drilling, the most intriguing Trump pivot could emerge on two lesser discussed but exponentially impactful frontiers – artificial intelligence and cryptocurrencies. Though lacking traditional visibility in a legacy policy portfolio, both domains showcase pillars of future global economic power and prosperity. As AI infiltrates nearly all industries and crypto capacities remake finance, Trump’s second-term choices sculpting their rise carry significance dwarfing other economic tinkering. In both cases, the current President’s “risk first and only” regulatory view of both sees possibly its greatest difference to an innovation and American-leadership focused agenda that could, beyond anything else covered here, radically alter the rest of the 21^st century.

On AI and associated machine learning algorithms, Trump possesses no innate affinity or historical fluency to guide these advances either more broadly or in terms of specific applications. But he shows latent savviness by generally abstaining from arbitrarily neutering innovators through premature regulation and framing these technologies first, and only, as risks, letting capital flow and breakthroughs emerge organically. Compared to less economically proficient regions rushing pell-mell standards more bureaucratic than practical, America enjoyed competitive advantage from Trump’s light governance touch so far allowing startups latitude proving concepts and securing public trust. This is in stark contrast to the Biden administration where they are focused on a ‘No, but we’ll let you in at some point once we’re out of office’ strategy.

Cryptocurrencies and their blockchain technologies inspire similar internal conflicts for team Trump, balancing openness towards financial system modernization against reflexive distrust of threatening change. There is an inherent conflict between Trump’s views on political and economic centrality and the fundamental decentralized philosophies in crypto.  Regulators across agencies like the Fed, FDIC, Treasury, SEC and CFTC guided under his watch fluently spoke crypto vernacular. Their proactive engagements to date crystallized a coherent posture acknowledging vast promise met equally by risks. Hence thoughtful policy evolution outpaces most nations. A Trump 2.0 administration with an expanded remit (especially with control of both houses of Congress which also appears to be ‘as given’ if he were to win again), staffing of agencies with expertise (most of which left during the first 2 years of the Biden admin) and clear policy goals would immediately lead to positive economic & political outputs.

But further opportunities emerge for more collaborating across government, academia and industry at this crossroads. Strategic choices in the next two years could determine whether revolutionary phases flourishing elsewhere eventually mature abroad then get imported back secondhand to America, ceding competitiveness—or whether confident public-private partnerships cement domestic innovation leadership underlying much of this century’s web3 transformation. The infrastructure to greatly expand public-private partnerships is already in place and more direct support from a Trump 2.0 would equally show immediate returns.

What might presidential leadership pursuing the latter look like? First, funding research and specialized education programs for AI & digital asset literacy, particularly in financially underserved communities allows traditionally excluded demographics accessing epochal opportunity. Second, encouraging upgrading legacy technologies in regulated areas to enable frictionless adoption makes intuitive sense and would extend American global leadership; doing so reinforces broader trust and equally important soft diplomacy gains. Third, establish clear regulatory guardrails that allow for restrictions in use and entry points for innovation for emerging technologies. Other targeted policy tweaks and streamlined rulemaking promise profoundly positive spillovers. See earlier comments I’ve made about the potential impact of the Supreme Court throwing out the doctrine - This change alone would radically alter the regulatory landscape.

Of course, critics will rightly warn against overreach or distortion from policy overcorrecting too crudely to bolster hypothetical projections. Change itself challenges many even where evidence shows net progress. And Trump himself owns no record showing savvy restraint whenever tantalized by a chance reshaping history exclusively by his moxie. Both technological frontiers highlighted here demand heightened emotional intelligence and disciplined collaboration beyond typical strongman tendencies. Of course, critics will rightly warn against overreach or distortion from policy overcorrecting too crudely to bolster hypothetical projections. Change itself challenges many even where evidence shows net progress. And Trump himself owns no record showing savvy restraint whenever tantalized by a chance reshaping history exclusively by his moxie. Both technological frontiers highlighted here demand heightened emotional intelligence and disciplined collaboration beyond typical strongman tendencies.

Yet the opportunity still blinks enticingly before his taking. The former (and potentially future) president owns this climate and these tools for canonizing a surprisingly enlightened economic legacy should he see wisdom in astutely shepherding seismic shifts already underway. Defying expectations of him for short-term self-service by wisely unleashing innovations destined to improve countless livelihoods would surprise his antagonists and reward open-minded supporters. And much as the brash billionaire reality star crafted an iconoclast political image seemingly hastening needed disruption of ossified systems, he may choose harnessing profound technological transformations for society’s betterment as an unlikely final act. Heroes emerge often where least expected, and perhaps a Trump 2.0 would lead to the most innovative technology lead expansion of American economic and political power since the end of the second World War. Time will tell.

The fear of AI seems to have stemmed directly from the concerns surrounding Big Tech, Social Media, and Cryptocurrency. The voices that once clamored about the threats posed by these technologies have now shifted their gaze towards AI, generating concerns that are largely based on speculative risks. These fears, rather than being rooted in solid evidence of AI's current implications, seem to be extrapolations from the issues faced in other areas of the digital realm.

This brings us to the administration's 'regulatory first' model. We have seen this strategy in action in other spheres, notably in the world of cryptocurrencies. Various government agencies, with the financial services sector at the forefront, are espousing a 'no first' stance. Rather than taking a proactive approach to understand and work with emerging technologies, the default response seems to be to say 'no' and impose restrictions. It is clear that more than a few people in the Biden (and previously Obama) administrations felt like they messed up how to respond to Social Media and now are over-correcting with something much broader, much more impactful.

While regulation is undoubtedly important to prevent abuse and protect society, the approach of constraining technology first, and encouraging it later, will limit the potential benefits that these technologies can offer. It is the responsibility of the regulatory bodies to strike a balance between the need to regulate and the importance of fostering innovation.

However, amid this focus on risk and regulation, several crucial issues seem to be left on the back burner. Take, for example, the potential disruptions that the current generation of AI might introduce, such as the commoditization of Deep Fakes and their potential impact on the forthcoming elections.

Deep Fakes, AI-powered manipulations of audio and video that can generate realistic, but entirely fake, media, pose a significant threat to the integrity of information in our society. The potential misuse of this technology in a political context, such as during an election, could have profound effects on our democracy.

Intriguingly, the stage has been set for this conversation with legislative precursors such as the 2023 National Defense Authorization Act (NDAA) and the proposed Blueprint for an AI Bill of Rights. The 2023 NDAA has incorporated crucial AI guidelines, suggesting that the government recognizes the potential of AI and is willing to integrate it into the nation's defense mechanism. Simultaneously, the AI Bill of Rights proposes to safeguard the rights of individuals against potential AI threats, providing a framework to ensure that AI systems operate within ethical boundaries, respecting privacy and freedom.

These policies depict a foresight and willingness to engage with AI's potential, not just its risks. They present a vision of a future where AI is integrated into our societal infrastructure, but with necessary protections to safeguard individual rights and maintain social order.

In contrast, Executive Order 13960, which focused on promoting the use of trustworthy AI in government, seems to lean more towards caution. The Order mandates rigorous risk assessment and management strategies before any AI systems can be employed. The emphasis on preemptive regulation paints a stark picture when compared to the forward-looking and integrative approach of the 2023 NDAA and the AI Bill of Rights.

This contrast raises questions about the administration's approach to AI. While regulation is essential, so too is creating an environment that allows the benefits of AI to be realized. Striking a balance between these two will be key to harnessing the full potential of AI. It's clear that the conversation around AI is evolving and it's crucial that we continue to engage in this discussion with an open and balanced perspective.

Further, there is the persistent issue of AI's impact on the job market, which we are just beginning to see. The automation of tasks by AI is likely to lead to job displacement in various sectors, and this potential upheaval requires significant attention and planning. We are already seeing it happen - a report from Challenger, Gray, and Christmas found that 3,900 people lost their jobs in May due to artificial intelligence (AI). This was the first time AI was listed in the monthly report…. and a first glance as to what the future will bring. These job losses will not be contained to any one market or subset of the workforce but will end up impacting nearly every person who works.

In summary, while the Biden administration's concerns about the risks of AI are valid, the emphasis should not be solely on regulation. It's essential that we also focus on understanding these technologies, addressing the most pressing threats they pose, and ensuring that our society is prepared to manage the disruptions they may cause. AI holds immense potential to improve our world, but only if we approach it with a balanced perspective that includes not only the risks but the opportunities and presents a cohesive way forward maximizing our nation’s opportunities to guide the global AI market moving forward. Education (both traditional and professional) needs significant focus and investment in all sectors to assist with this transition.

1. Woah, AI can be used for criminal activities? I had no idea! (I know! Shocking, right?!)

2. I’m a policy person. What new policies restricting AI use should we write? (I am not convinced that regulating AI in the US is a good idea.)

3. I’m a startup person in AI. How do I ensure I get funded for this in 2023? (My short answer - don’t bother.)

4. I’m a media producer. Can you come talk on (insert show) about this? (Sure!)

So, let’s dig into this and discuss some of the biggest uses of AI for criminal activities (in no particular order):

1. Ransomware attacks: Ransomware attacks, in which attackers encrypt a victim's data and demand a ransom for the decryption key, have become increasingly prevalent in recent years and are likely to continue to be a major threat in the future. AI is becoming a huge accelerator here - from specific organizational or individual targeting, AI is now being used to identify categories of targets and automating the attack vectors.

2. Supply chain attacks: Supply chain attacks, in which attackers compromise the software or hardware of a vendor in order to gain access to the systems of their customers, have also become more common and are likely to continue to be a significant risk in the coming years. AI is being used in two very interesting ways. First, by having the AI create and then insert subsets of ‘bad’ code into devices so that traditional antivirus/spyware/etc. tools can’t use traditional signatures to find it; and second, similar to ransomware, identifying categories of potential targets and automating the attacks.

3. Cloud security: As more and more organizations (especially large corporations, governments and financial services institutions) move their data and applications to the cloud, the security of cloud-based systems is likely to become an increasingly important concern. The lag that these groups have experienced in moving to the cloud has increased, not decreased, the overall risk. As such, the criminal element is making use of automated AI systems to identify less secure environments and targeting the ‘lift and shift’ legacy technology programs that it can identify. 

4. Internet of Things (IoT) security: The proliferation of connected devices, including smart home appliances and industrial control systems, is likely to continue to be a source of risk as these devices often have poor security measures in place. Take the cloud security note above and apply it here, except the risks are higher, baseline security is lower and the pace of migration is faster. This is the biggest ‘back office’ concern I have.

5. Deepfakes: The ability of criminals to use deepfakes to automate the compromising of individuals - both in terms of getting access to personal accounts as well as using them to open the doors to other, broader enterprise or government access. Deepfakes coupled with natural language processing (NLP), machine learning (ML) and the massive amount of data out there makes this a huge concern. When I was a federal employee, someone pretending to be me called our HR group with enough personal info that if it hadn’t been for a thoughtful HR employee, my paycheck would have ended up being sent to a fintech company sitting in front of a Banking as a Service provider with less than stellar risk management. Now, imagine that being entirely automated and millions of people being targeted automatically on a daily basis… Please make sure you have multi-factor authentication on all your cellular and financial services accounts, kids.

Well now that I’m properly depressed, I’m going to leave it here. Where would you all like me to take this discussion?